Lead Python developer AWS cloud & AI

Title:

Lead Python developer with AWS cloud & AI-based experience Term:
Contract

We need strong candidates who have developed LLMs, Designed workflows and AI tools deployment knowledge.

• 5+ years of experience building production-grade systems with end-to-end ownership
• Strong expertise in Python and software engineering best practices

Join a horizontal engineering team supporting 600+ application teams on a mission to elevate engineering maturity across the organization. This team drives standards, guidelines, platform capabilities, and large-scale technical debt remediation.

In this role, you will develop advanced agentic AI workflows to automatically analyze codebases, detect technical debt, and generate high-quality fixes—from vulnerability patches to dependency and language upgrades. This is a hands‑on, high‑impact opportunity to shape the future of automated software modernization.

• Design, develop, and maintain LLM-powered multi‑agent workflows for code analysis, remediation proposals, and safe patch generation
• Implement agentic patterns such as planning/execution loops, tool orchestration, sandboxing, guardrails, and failure recovery
• Build scalable automation systems for technical debt remediation, including language/runtime upgrades, dependency modernization, vulnerability patching, and configuration drift correction
• Collaborate with Developer Experience and Platform teams to define engineering standards and reusable best practices
• Architect and optimize RAG pipelines, including chunking strategies, embeddings, hybrid search, reranking, and retrieval policies
• Develop evaluation frameworks for LLMs, RAG, and multi‑agent workflows, including offline datasets, validation metrics, statistical testing, and A/B experiments
• Contribute to backend systems using Python, distributed systems, microservices, Postgre
  
  SQL, DBT, vector databases, caching, streaming, and queueing technologies
• Build CI/CD pipelines, observability dashboards, and conduct performance analysis across model, retrieval, and network layers
• Work cross‑functionally with product, platform, and security teams to take prototypes to production‑grade services
• Communicate effectively with stakeholders, produce high‑quality technical documentation, and mentor junior engineers

• 5+ years of experience building production‑grade systems with end‑to‑end ownership
• Expertise in Python, software engineering best practices, testing strategies, CI/CD, and system design
• Hands‑on experience shipping LLM‑powered features (e.g., autonomous workflows, function calling) with measurable reliability or latency improvements
• Strong understanding of multi‑agent architectures including planners, executors, and tool routing
• Deep knowledge of RAG systems: chunking, embeddings, vector/hybrid search, retrieval policies
• Experience evaluating LLMs and agent workflows using statistical reasoning and validation techniques
• Proficiency with AWS (Lambda, ECS/EKS, S3, API Gateway, EC2, IAM) and Infrastructure‑as‑Code
• Experience with observability tools (e.g., Datadog) covering logging, tracing, and metrics
• Familiarity with Postgre
  
  SQL, DBT, data modeling, schema evolution, and performance tuning
• Knowledge of vector databases such as Pinecone or pgvector
• Experience designing or optimizing CI/CD pipelines (Git Hub Actions or similar)
• Proven track record in application modernization, dependency management, and technical debt reduction
• Ability to rapidly prototype, validate, and transition solutions into production

• Experience designing agent infrastructure with sandboxing, tool isolation, and fail‑safe execution
• Background in large‑scale platform engineering or developer experience tooling
• Understanding of enterprise AI security, compliance, and privacy requirements
• Strong architectural communication skills, including RFC development and technical diagramming

• Adaptable, proactive problem solver
• Strong ownership mindset with excellent collaboration and communication skills
• Comfortable working in fast‑paced, ambiguous R&D environments
• Passionate about building high‑leverage platform capabilities that support hundreds of engineering teams