Python Developer
Listed on 2026-02-16
-
Software Development
AI Engineer, Machine Learning/ ML Engineer
Overview
At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & Dev Ops, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our Fin Labs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile‑first applications and more.
Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets.
The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Charlotte NJ $120K-$125K/year & benefits (see below).
RoleTechnical Lead – Python & AI/ML
LocationNYC, NY
Job Overview- We are looking for a highly capable Technical Lead – Python & AI/ML with deep expertise in backend engineering, LLM‑based applications, RAG architectures, and AI agent frameworks.
- You will lead the design, development, and deployment of production‑grade AI systems built on Python, modern LLM tooling, retrieval engines, embeddings, and vector databases.
- This is a hands‑on leadership role focused on building scalable and intelligent AI products.
- Lead the architecture and development of LLM‑driven applications, AI agents, and RAG‑based systems.
- Provide technical guidance, conduct code reviews, and mentor junior team members.
- Drive best practices in Python backend engineering, API development, and AI system design.
- Build and maintain backend services using FastAPI or Flask
. - Develop scalable API endpoints for AI applications, embeddings, and retrieval systems.
- Ensure backend code quality, modularity, performance, and maintainability.
- Build AI applications using:
Lang Chain, Lang Graph, Semantic Kernel, Haystack, Llama Index, Auto Gen - Develop autonomous or semi‑autonomous AI agents with tool calling and workflow graphs.
- Implement Retrieval‑Augmented Generation (RAG), embedding pipelines, chunking strategies, reranking, and grounding techniques. >
- Manage prompt engineering, prompt routing, safety guardrails, and evaluation metrics.
Work with OpenAI SDK and other LLM providers (Anthropic, Azure OpenAI, Cohere, etc.).
- Build data pipelines for indexing, embeddings, and retrieval workflows.
- Work with SQL databases (Postgre
SQL, MySQL, etc.) for metadata and application storage. - Work with vector databases such as:
Redis
, Postgres with pgvector
, Elasticsearch
, Neo4j
, or others. - Implement and optimize search workflows using FAISS or similar similarity search libraries.
- Deploy AI services using Docker, container orchestration, and cloud environments.
- Implement monitoring for AI behavior, performance, error rates, and retrieval accuracy.
- Set up CI/CD pipelines for backend and AI components.
- Optimize inference cost, latency, and reliability.
- Collaborate with product, data engineering, and business teams to understand requirements.
- Translate business problems into scalable AI architectures and deliver practical solutions.
- Communicate technical decisions, trade‑offs, and progress to stakeholders.
- Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related fields.
- 10+ years of experience in Python backend development
. - Strong proficiency in FastAPI or Flask
. - Strong working knowledge of SQL databases (Postgres, MySQL, etc.).
- Hands‑on expertise with vector databases
: - Redis
, Postgres/pgvector
, Elasticsearch
, or Neo4j
. - Practical experience with FAISS for similarity search.
- Hands‑on…
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