Middle AI/ML Engineer (GenAI, AWS)

Provectus is an AWS Premier Consulting Partner and AI consultancy featured in Forrester's AI Technical Services Landscape, with 15+ years of experience and 400+ engineers. We build production AI for global enterprises in partnership with Anthropic, Cohere, and AWS. As a Middle ML Engineer at Provectus, you will design, build, and deploy production ML solutions for our clients — working independently on most tasks while growing toward senior technical ownership. You'll use AI coding tools daily, mentor junior engineers, and contribute to Provectus's internal AI toolkit. What You'll Do: **Build & Ship ML (55%)*** Design and deliver ML pipelines from experimentation to production; * Build and optimize models — supervised, unsupervised, and generative AI; * Write clean, tested, modular Python code; * Deploy and monitor models; track performance and prevent drift; * Contribute to LLM applications: RAG systems and agent workflows; * Use AI coding tools on every task to move faster and write better code. **Agentic & AI-Assisted Engineering (20%)*** Use Claude Code or similar AI tools to deliver client projects; * Build with agent frameworks (Bedrock AgentCore, Strands, CrewAI, or similar); * Integrate or build MCP servers for internal and client use; * Contribute features, bug fixes, or docs to the Provectus AI toolkit. **Collaborate & Mentor (15%)*** Mentor junior engineers and give actionable code review feedback; * Work closely with DevOps, Data Engineering, and Solutions Architects; * Share knowledge through docs, presentations, or internal workshops. **Learn & Innovate (10%)*** Stay current with ML research, GenAI, and agentic frameworks; * Propose process improvements and reusable ML accelerators; * Participate in architectural design and trade-off discussions. What You Need: **Machine Learning*** Solid grasp of supervised/unsupervised ML: algorithms, evaluation, trade-offs; * Deep learning hands-on experience: CNNs, RNNs, Transformers — training and fine-tuning; * Depth in at least one domain: NLP, Computer Vision, Recommendation, or Time Series. **LLMs & Generative AI*** Experience building LLM apps with OpenAI, Anthropic, or Hugging Face APIs; * Hands-on RAG design: chunking, embedding, retrieval, generation; * Familiarity with vector databases (OpenSearch, Pinecone, Chroma, FAISS); * Understanding of prompt engineering and LLM evaluation. **Agentic Engineering (Required)*** Proficient with AI coding tools (Claude Code, Cursor, Copilot, etc.) — beyond autocomplete; * Experience building tool-using, stateful agents with an orchestration framework; * Understanding of Model Context Protocol (MCP) — consume or build MCP servers; * Can write technical specs for AI execution and review/correct AI-generated output; * Aware of agent monitoring, evaluation, and cost optimization in production. **Cloud & Infrastructure*** Solid AWS: SageMaker, Lambda, S3, ECR, ECS, API Gateway; * Familiarity with Amazon Bedrock (model invocation, Knowledge Bases, Agents); * Basic awareness of Infrastructure as Code (Terraform or CloudFormation). **MLOps & Data*** Production ML deployment experience; * Experiment tracking with MLflow, W&B, or similar; * CI/CD pipelines for ML; model monitoring and drift detection; * Advanced Python (async/await, OOP, packaging); strong pandas, NumPy, SQL; * Docker for containerized ML workloads. **Experience & Education*** 1–3 years of hands-on ML engineering experience; * At least one ML model deployed to production (or near-production); * Team-based or client-facing project experience; * Demonstrated use of AI-assisted development tools; * Education: Bachelor's/Master's in CS, Data Science, Math, or equivalent practical experience. **Key Traits*** Strong problem-solver — breaks complexity into testable pieces; * Clear communicator — written docs, PRs, and explanations to non-technical stakeholders; * Fluent English (B2+); * Proactive — raises blockers early and comes with proposed solutions; * Collaborative mentor who helps without creating dependency. **Nice to Have*** AWS certifications; * Kubernetes experience; * GraphRAG or custom MCP server experience * Open-source contributions or published work on agentic systems. What We Offer: * Competitive salary based on competencies and market rates; * Premium AI tooling: Claude Code, Cursor, and Provectus AI toolkit; * Mentorship from Senior ML Engineers and Tech Leads; * Clear growth path: Mid-Level → Senior ML Engineer → Tech Lead; * Learning budget for courses, certifications, and conferences; * Remote-first culture; work on projects across LATAM, North America, and Europe; * Health benefits.