Senior Software Developer(Python)
Summary
Build and ship AI-powered agentic applications using Python, LangChain/LangGraph, and vector databases; lead system design, DevOps, and team mentorship.
Overview
Role: Senior Software Developer(Python)
Location: Hybrid/Remote
Experience: 5-7 Years
Reports to: Founder / Engineering Head
About Our Client
Our client is a fast-growing AI-driven technology company focused on building scalable, enterprise-grade solutions. They specialize in AI systems, cloud architecture, and custom software development for global clients.
Responsibilities
- End-to-end solution design — from architecture planning to post-deployment optimization
- Lead engineering execution alongside architecture (hands-on role)
- Own DevOps, CI/CD pipelines, and deployment processes
- Drive performance optimizations across the engineering stack
- Build and ship real-world, user-facing AI/agentic applications
- Take end-to-end product ownership, including partner-facing deliverables
- Lead and mentor the engineering team
- Design and implement multi-agent orchestration architectures — including agent routing, task delegation, memory, and inter-agent communication patterns
- Architect semantic layers — knowledge graphs, vector stores, retrieval pipelines, and structured data abstraction for AI consumption
- Present and explain architecture decisions clearly to both technical and non-technical stakeholders
Must-Have Technical Skills
- Python (primary language — must be strong)
- System design (non-negotiable — must be top-notch)
- Agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen, or similar)
- Proven experience building agentic AI applications end-to-end
- Multi-agent orchestration — designing supervisor/worker agent hierarchies, tool-use patterns, and stateful agent workflows
- Semantic layer architecture — RAG pipelines, embedding strategies, vector databases (Pinecone, Weaviate, pgvector), and knowledge retrieval design
- GenAI system design — ability to architect scalable LLM-powered systems, including prompt pipelines, context management, model routing, and output validation layers
- GenAI infrastructure — experience designing for latency, cost, and reliability trade-offs across LLM providers (OpenAI, Anthropic, Gemini, open-source models)
- DevOps & CI/CD (GitHub Actions, Docker, Kubernetes, or equivalent)
- Post-deployment monitoring, scaling, and optimization
Experience
- Minimum 5+ years, strongly preferred 7+ years
- Must have shipped real-world, user-facing products (not just internal tools or prototypes)
- Proven team lead experience
Nice to Have
- Experience with cloud platforms (AWS / GCP / Azure)
- Background in AI product development or AI startups