We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

We are hiring a senior full-stack engineer for a HIPAA-compliant healthcare SaaS platform that is already in production and still adding core features. You will build and maintain the Django backend, REST APIs, and PostgreSQL data layer, and ship the corresponding Next.js and React UI. Part of the work is integrating Azure AI for document intake and clinical insights. You will also own infrastructure and delivery: Terraform, Docker, Kubernetes, CI/CD pipelines, and Playwright end-to-end tests. The main focus is production quality—secure APIs, performance, observability, and a system that stays reliable as usage grows. We need someone who has shipped healthcare or other regulated products and can work independently across backend, frontend, and cloud.

Hands-On Lab Tester / Technical QA Specialist Company Opsgility Position: Hands-On Lab Tester / Technical QA Specialist Job Type: Part time/Contract Location: Remote About SkillMeUP.ai SkillMeUP.ai is a hands-on technical learning platform designed to help individuals and organizations build practical skills in cloud computing, cybersecurity, artificial intelligence, Microsoft technologies, and other enterprise IT platforms. Our labs provide learners with real cloud environments where they can follow guided exercises, configure resources, troubleshoot systems, and develop real-world technical skills. Position Overview Opsgility (our product is SkillMeUP.ai) is seeking a Hands-On Lab Tester / Technical QA Specialist to test technical training labs before they are released to learners. The Lab Tester will work through labs exactly as a student would, verifying that instructions are accurate, cloud resources provision correctly, exercises can be completed successfully, and the overall learner experience is clear and reliable. This role is ideal for someone who enjoys working with cloud technologies, following technical instructions, troubleshooting problems, and identifying ways to make technical content easier to understand. Responsibilities * Execute SkillMeUP.ai labs from beginning to end as a learner would. * Verify that lab environments provision and initialize correctly. * Follow lab instructions exactly as written and identify missing, confusing, or inaccurate steps. * Validate Azure, Microsoft 365, Power Platform, AI, cybersecurity, and other technical lab environments. * Confirm commands, scripts, configuration steps, URLs, screenshots, and expected results. * Identify technical errors, broken instructions, permissions issues, provisioning failures, and platform problems. * Verify that lab resources, accounts, credentials, and permissions are available when required. * Test labs using the SkillMeUP.ai browser-based lab environment and remote desktop interfaces. * Record the actual time required to complete each lab and compare it with the estimated duration. * Document defects with clear reproduction steps, screenshots, error messages, and recommended corrections. * Retest labs after fixes are implemented. * Evaluate labs from a learner's perspective and identify areas where instructions could be clearer. * Test labs after Microsoft, Azure, or other vendor interfaces and services change. * Work with course authors, engineers, and platform developers to resolve issues. * Maintain testing checklists and report lab readiness prior to publication. What You'll Test Labs may include technologies such as: * Microsoft Azure * Microsoft 365 * Microsoft Copilot * Microsoft Entra ID * Microsoft Intune * Azure AI and Microsoft Foundry * Power Platform * Windows Server * Linux * Networking * Cybersecurity * Git and GitHub * Containers and Kubernetes * DevOps * Databases * Artificial intelligence and machine learning Candidates are **not expected to be experts in every technology**. The ability to learn quickly, carefully follow technical instructions, and troubleshoot problems is more important. Required Qualifications * General understanding of IT, cloud computing, networking, operating systems, or software development. * Comfortable working with web-based administration portals and technical tools. * Ability to follow detailed technical instructions precisely. * Strong troubleshooting and problem-solving skills. * Excellent attention to detail. * Ability to clearly document problems and explain how they can be reproduced. * Comfortable using command-line tools such as PowerShell, Bash, or Azure CLI. * Ability to distinguish between a problem with the lab instructions, the cloud environment, and the SkillMeUP.ai platform. * Strong written English communication skills. * Ability to work independently in a remote environment. Preferred Qualifications Any of the following are helpful but not required: * Experience with Microsoft Azure. * Microsoft, CompTIA, AWS, Google Cloud, ISC2, or other technical certifications. * Experience with technical training or certification courses. * Experience performing software QA or user acceptance testing. * Experience administering Windows or Linux systems. * Experience with Microsoft 365 or Power Platform. * Familiarity with GitHub and DevOps tools. * Experience completing hands-on technical labs, bootcamps, or certification training. What Makes Someone Successful in This Role The best Lab Testers are naturally curious and detail-oriented. They don't simply determine whether a lab "works." They ask questions such as: * Can a student successfully complete this without outside help? * Does every instruction match what is actually displayed on screen? * Are there assumptions the author forgot to explain? * Did the cloud environment provision correctly? * Are permissions and credentials correct? * Does the expected result actually occur? * Could a confusing instruction cause a learner to make a mistake? * Has a Microsoft or cloud-service update changed the procedure? * If something fails, can another team member reproduce the problem from the tester's report? ## Example Testing Workflow A Lab Tester may be assigned a 60-minute Azure lab and will: 1. Launch the lab through SkillMeUP.ai. 2. Verify the assigned cloud environment and credentials. 3. Complete every instruction exactly as written. 4. Verify each expected result. 5. Record any errors or confusing instructions. 6. Capture screenshots and error messages where appropriate. 7. Record the actual completion time. 8. Submit a testing report with pass/fail results and identified defects. 9. Retest the lab after corrections have been made. ## Success Metrics Performance in this role may be measured by: * Percentage of labs thoroughly tested prior to release. * Accuracy and completeness of defect reports. * Number of learner-impacting issues identified before publication. * Ability to reproduce and clearly document failures. * Lab retest turnaround. * Accuracy of lab completion-time estimates. * Quality and usability of feedback provided to course authors and engineers. Why Join Opsglity You'll have the opportunity to work directly with emerging cloud and AI technologies while helping ensure thousands of learners receive a reliable, high-quality hands-on training experience. This is an excellent position for someone who enjoys technology, continuous learning, troubleshooting, and working with real cloud environments.

We are seeking a Forward Deployed Engineer to own full client engagements from pre-sale with a hot lead through delivery and handover. This role combines 60% software engineering with 40% strategic ownership. You will design solutions, build and maintain CI/CD pipelines, assess technical risk, and manage production incidents. You should have 7+ years of experience shipping real-world software. We are tech-agnostic, meaning we are open to considering candidates with diverse technology backgrounds — .NET/C#, Java, Python, Node.js, or similar. While .NET/C# is our primary backend language and Angular our primary frontend framework, prior experience with either is not mandatory — Vue, React, or similar works just fine., with strong backend proficiency in .NET (C#), and experience with cloud platforms. You must also be proficient in production AI integrations, including RAG systems, LLM APIs, agents, and vector databases. You will communicate directly with clients, so having experience in direct client communication is a must; also run requirement discovery sessions, and translate technical constraints into business value without a PM or BA intermediary.

Summary Role Level: IC4 Senior Security Administrator I (US Contract) Reports to: Manager of Engineering Services Salary: $50/h Job Description he Security Administrator role supports BEMO managed service customers and internal teams by assisting in the implementation, management, and monitoring of security and compliance solutions across Microsoft 365 and hybrid environments. This role is focused on a security-centric customer base, and we are specifically seeking candidates with experience working in GCC High tenants. In this role, you will also have the opportunity to lead compliance frameworks, including SOC 2, ISO, and CMMC, by maintaining security and compliance requirements across regulated environments. The Security Administrator II IC4 will demonstrate the ability lead practices within the following areas: • Microsoft 365 Security Administration • Azure • GRC Platforms • AI tools • Customer Service • Managed Services • Team Communication • Data Gathering and Analysis At BEMO, the Security Administrator IC4 competencies require: • In- depth specialist knowledge in your area of expertise. • Skilled problem solver and critical thinker when faced with unfamiliar challenges. • Makes informed, data-driven decisions. • Clear and open communicator across teams and departments. • Builds highly effective working relationships across the organization. • Continuously seeks expertise from peers and external sources. Responsibilities & Primary Goals • Monitoring and Maintenance o Proactively secure Microsoft 365 and Azure environments o Monitor all security systems and provide advice on strategy and implementation for the customer base o Conduct security risk and vulnerability assessments on security package customers o Enforce data governance o Patch and vulnerability-managed life cycle o Implement updates programmatically on different security packages offered by BEMO o Send out customer communications on security improvements and maintenance • Automation and Implementation of Managed Service Solutions o Create and document repeatable processes through automation across our managed service maintenance activities o Manage internal projects, provide technical guidance o Must be comfortable performing multiple initiatives simultaneously in a fast-paced environment o Leverage AI and automation technologies to optimize processes, improve response times, and enhance overall managed service delivery • Cross-Group Collaboration and Support o Support the Customer Success team with customer-specific data for security scores and value realization efforts o Provide T1-T2 Team members support for tickets and issues relevant to managed service customers' security and compliance o Working with the BEMO IT Manager to align security policies and processes o Work collaboratively with delivery engineers, operations team members, customer success managers, support engineers, and our BEMO customers o Manage support queue during designated times • Managed Security o Triage: Working with our SOC team and Microsoft Sentinel, you will help filter the noise to prioritize incidents and alerts that matter to alleviate alert fatigue. o Investigate: Investigate and analyze the most critical incidents, and document progress and findings. You will be analyzing logs within M365 tools and Sentinel. o Respond: Contain and mitigate incidents faster with managed response and proactive remediation. o Prevent: Provide detailed recommendations and best practices to go beyond detection and response to prevent future attacks. Requirements • Educational degree or diploma in Computer Science, Engineering, or the equivalent in proven experience • 5 + years of experience administrating, managing, and implementing Microsoft Azure and Microsoft 365 as an implementation, security, or support engineer. • Experience analyzing M365 usage data to identify issues and usage patterns • Strong critical thinking, analysis, and problem-solving skills • Strong competency in core professional skills, especially attention to detail, responsiveness, follow-through, and flexibility, with a high degree of emotional intelligence and tact • Ability to work independently and collaboratively with other internal teams when needed • Proven customer service experience with clear and consistent writing, presentation, and communication skills • Azure Cloud experience Specialized Knowledge or Skills Preferred • A Bachelor of Science or Engineering in Computer Science or a related field preferred • Microsoft certifications are required (AZ-500, SC-300, SC-400, etc.)

Title: DevSecOps / Platform Security Engineer — Kubernetes, Supply-Chain Security, Accreditation (Contract) Category: DevOps Engineering / Kubernetes / Security Description: We're building a multi-agent AI orchestration platform for defense and mission-critical operations, currently working toward a higher security accreditation level on a hardened government-focused deployment platform. We need an experienced DevSecOps engineer for a contract engagement to harden the platform and move our accreditation evidence pipeline forward. This is an interim, contract-only engagement. We're running a separate process to fill a permanent role, and this project is scoped independently of that. What you'll do: Contribute to our secure release pipeline: automated builds, hardened base images, artifact signing, provenance tracking, and software bill of materials generation feeding a weekly release cycle Harden platform authentication, pod security, and secrets handling Work with container image scanning and software supply chain security tooling Help turn scan results and provenance data into accreditation evidence Work with Kubernetes, Helm, GitOps-based delivery, and infrastructure as code What we're looking for: 5+ years in DevSecOps, platform, or infrastructure engineering Strong production Python experience (API frameworks, CLIs) Deep Kubernetes experience: image hardening, pod security, Helm and GitOps workflows Hands-on CI/CD and software supply chain security tooling experience Nice to have: federal risk management framework or accreditation experience; familiarity with AI agent platforms or agent tool-calling protocols Engagement details: Remote, contract — no security clearance required U.S. work authorization required

# Upwork Job Posting ## Go-to-Market (GTM) Engineer – AI, Automation & Growth for Customs Brokerage (3-Month Contract) ### About Us We are a fast-growing U.S. Customs Brokerage and Trade Compliance firm looking to transform how importers find and work with customs brokers. Our vision is to become one of the most technology-driven customs brokerages in the United States by leveraging AI, automation, and data to improve customer acquisition, client experience, and operational efficiency. We are looking for an experienced **Go-to-Market (GTM) Engineer** who can combine software engineering, AI, sales automation, and growth strategies into scalable systems. This is **not** a traditional marketing position. You will be building technology that generates revenue. --- # Contract Duration **3 Months (with potential for long-term engagement)** Expected commitment: * 20–40 hours per week * Flexible schedule * Remote --- # Project Goals By the end of this contract, we want to have a repeatable system that: * Generates qualified importer leads * Automates outbound prospecting * Tracks and nurtures prospects * Uses AI to personalize communications * Integrates sales, marketing, and CRM workflows * Provides dashboards for business performance --- # Responsibilities You will design and build systems including: ### 1. Importer Lead Generation * Build databases of U.S. importers * Analyze import data * Score potential customers * Identify high-value prospects * Build workflows for ongoing lead generation --- ### 2. CRM & Sales Automation Integrate and automate platforms such as: * HubSpot * Pipedrive * Salesforce * Airtable * Notion Create workflows for: * Lead routing * Email sequences * Pipeline automation * Follow-up reminders * Customer lifecycle management --- ### 3. AI Sales Automation Build AI-powered systems that can: * Research prospects * Generate personalized cold emails * Draft LinkedIn outreach * Prepare sales call notes * Summarize meetings * Recommend follow-up actions Experience with OpenAI APIs, Claude, Gemini, or similar AI platforms is highly desirable. --- ### 4. Data Engineering Develop pipelines using: * Python * APIs * SQL * Web scraping (where appropriate and compliant) * ETL workflows Build importer intelligence databases that combine: * Company information * Import activity * Contact enrichment * Lead scoring --- ### 5. Business Intelligence Create dashboards showing: * Lead generation * Conversion rates * Sales pipeline * Revenue metrics * Customer acquisition cost (CAC) * Marketing ROI --- ### 6. Website Growth Recommend and implement tools that improve conversion, such as: * Interactive duty calculators * Customs compliance checklists * HTS lookup tools * AI chat assistants * Lead capture forms * Landing pages --- ### 7. Automation Automate repetitive business tasks using tools such as: * n8n * Zapier * Make * Python scripts * APIs --- # Technical Requirements Strong experience with several of the following: * Python * JavaScript/TypeScript * SQL * REST APIs * OpenAI API * LangChain or similar AI frameworks * HubSpot * Zapier * n8n * Make * Git/GitHub * Docker (preferred) * Cloud platforms (AWS, Azure, or GCP) * Web scraping * Data visualization --- # Nice to Have Experience in one or more of these industries: * Customs Brokerage * Freight Forwarding * Logistics * Supply Chain * International Trade * B2B SaaS Knowledge of: * U.S. Customs (CBP) * HTS Classification * ACE * Import/Export Compliance is a major advantage but not required. --- # Deliverables ## Month 1 * Understand business processes * Build CRM structure * Develop importer database * Set up AI workflows * Build first lead generation pipeline * Deliver initial dashboard *Launch automated outbound campaigns --- ## Month 2 * Build AI prospecting assistant * Create reporting dashboards * Integrate CRM automations * Develop customer scoring model --- ## Month 3 * Optimize workflows * Build additional AI tools * Document systems * Train internal team * Deliver production-ready automation stack --- # Success Metrics At the end of the contract we expect to have: * A scalable lead-generation engine * Automated outreach workflows * Centralized CRM * AI-assisted sales processes * Real-time reporting dashboards * Documented systems ready for long-term growth --- # What We're Looking For We value builders who enjoy solving business problems with technology. You should be comfortable working independently, proposing ideas, and delivering practical solutions rather than waiting for detailed instructions. If you've built growth systems that combine AI, automation, software engineering, and sales, we'd love to hear from you. --- ## To Apply Please include: 1. A brief introduction about yourself. 2. Examples of AI or automation projects you've built. 3. Links to GitHub, portfolio, or case studies (if available). 4. Your experience with CRM integrations and sales automation. 5. Your preferred hourly rate. 6. Why you're interested in this project.

I need a possible zero error high end Virtual Technology Boutique that is based on my artist name Venomista. I would like it to be up and running in next six months. It is multi level boutique that houses everything from electronics,wigs,nails,doll and dollhouse,and high-end computers and accessories. I need someone that can handle the job on their own to limit errors and delay in getting final product.

About us: Luxe Intelligence is a Baltimore based AI consulting firm. We design and deliver custom AI agent systems for business clients, including regulated industries, with a growing security and government-adjacent practice. We design the system and own the client relationship. You build to spec. The kind of work: Real examples of project types on our roadmap: - Data matching and compliance checking agents that cross-reference large lists (10,000+ rows) with no shared ID, using fuzzy name matching, confidence scoring, and human review flags - Research agents that pull from defined sources and produce structured memos with citations, and say "unverified" instead of guessing - Workflow automations across webhooks, spreadsheets, CRMs, Slack, and email - Read and write-back integrations with systems of record like Salesforce - Deployments inside client cloud environments with audit logging and security review support Must haves: - Strong Python, including pandas and API work - Hands-on experience with LLM APIs (Anthropic, OpenAI): prompt design, structured outputs, cost control - Fuzzy matching or entity resolution experience on real data - Cloud deployment on AWS, Azure, or GCP - Security-minded engineering as a habit, not an afterthought: secrets management, least-privilege access, encryption in transit and at rest, audit trails, human-in-the-loop review steps - Clear written English and documented handoffs Nice to have: - A real cybersecurity background: security engineering, compliance frameworks (SOC 2, NIST, FedRAMP awareness), or secure deployment in regulated environments - US citizenship with eligibility for a government security clearance, or an active clearance, is a plus and worth mentioning - Make.com or similar automation platforms - Salesforce API - Experience answering client security questionnaires How we work: Fixed-price milestones scoped from agreed hour estimates, paid on delivery and approval. NDA signed before any project details are shared. No client contact; all communication runs through Luxe. Some overlap with US Eastern hours. Every engagement starts with one small paid test milestone. Strong performance can grow into a larger ongoing role. To apply, answer these four things, and start your reply with the word CHARCOAL so we know you read this far: 1. Describe a fuzzy matching or entity resolution project you built. How big was the data, and how did you score confidence? 2. Describe an LLM-powered system you deployed into someone else's environment. What broke, and how did you fix it? 3. Estimate this: two lists, about 10,000 rows and 2,000 rows, no shared ID. Need matches, confidence scores, and a monthly flagged-items report. Roughly how many hours, broken down however makes sense to you? 4. Your hourly rate, your weekly available hours, and any security or clearance background.

Lead the development of an AI-agent platform that autonomously analyzes financial transactions, customer activity, cash flow, and risk signals to support FinTech operations. The system will use LLM-based agents, ML models, RAG, and real-time financial data to investigate anomalies, assess risk, generate financial insights, and recommend actions. Key Responsibilities: Define the AI-agent architecture, product roadmap, agent workflows, and evaluation strategy. Design specialized agents for fraud investigation, transaction analysis, risk assessment, cash-flow analysis, and financial reporting. Combine deterministic financial rules with ML predictions and LLM reasoning rather than relying solely on LLM outputs. Build agent orchestration using LangGraph/LangChain, tool calling, structured outputs, memory, and RAG. Develop ML pipelines for anomaly detection, behavioral scoring, transaction classification, and risk prediction. Implement human-in-the-loop approvals, confidence scoring, audit trails, and agent observability. Establish evaluation frameworks for agent accuracy, hallucination detection, tool-use reliability, and financial decision quality. Work with engineering teams to productionize agents using Python, FastAPI, PostgreSQL, AWS, Docker, and MLflow. Core Technologies: Python, PyTorch, Scikit-learn, XGBoost/LightGBM, LangGraph, LangGraph, LLMs, RAG, vector databases, PostgreSQL, FastAPI, AWS, Docker, MLflow, REST APIs, Databricks, and event-driven architectures. Core ML Libraries: - Deep Learning: TensorFlow, PyTorch, Lightning - Classical ML: Scikit-learn, XGBoost, LightGBM - NLP/LLMs: Hugging Face Transformers, spaCy - Hyperparameter Tuning: Optuna, Ray Tune Infrastructure & Tools: - Cloud: AWS/GCP/Azure (S3, BigQuery, Sagemaker) - MLOps: MLflow, Kubeflow, Prefect - Data: SQL, Pandas, PySpark, Dask - Deployment: Docker, Kubernetes, FastAPI Expected Outcome: A production-ready multi-agent FinTech intelligence system where AI agents investigate financial events, combine ML predictions with financial rules, retrieve supporting data, explain their reasoning, and route high-risk decisions to human reviewers. Skills Artificial Intelligence (AI) Machine Learning AI Agent Development RAG PyTorch Scikit-learn Databricks MLOps