Job Title: Gen AI Developer

Responsibilities

- Design, build, and deploy agentic AI systems capable of autonomous reasoning, tool use, and multi‑step task execution.
- Develop and maintain RAG (Retrieval‑Augmented Generation) pipelines, including retrieval strategies, vector indexing, and knowledge‑grounded AI applications.
- Build and orchestrate workflows using agentic frameworks such as LangGraph, LangChain (LCEL), AutoGen, crewAI, or similar platforms.
- Implement Model Context Protocols (MCPs) for tool integrations, API orchestration, structured system interactions, and scalable agent execution.
- Translate ambiguous business problems into robust, modular, and production‑ready agentic solutions.
- Evaluate and optimize agent performance, memory, planning, reasoning depth, hallucination reduction, and cost efficiency.
- Collaborate with ML engineers, platform engineers, and product teams to integrate agentic systems into enterprise platforms.
- Establish LLMOps / AgentOps best practices, including monitoring, observability, versioning, guardrails, and safety policies.
- Document system architectures, reasoning flows, and integration contracts for technical and non‑technical stakeholders.

Technical Skills – Must Have:

- Strong understanding of Agentic AI architectures, including planning, reflection, tool usage, multi‑agent collaboration, and decision loops.
- Hands‑on experience with RAG systems: embeddings, chunking strategies, hybrid retrieval, reranking, and evaluation.
- Advanced proficiency in Python, with experience building production‑grade AI services and automation layers.
- Practical experience with LangGraph, LangChain, AutoGen, crewAI,



or similar agentic frameworks.
- Proven expertise in implementing MCPs, tool registries, API connectors, and external system integrations for agents.
- Deep experience working with LLMs (OpenAI, Anthropic, Azure OpenAI, Llama), including prompt engineering, tool calling, and structured outputs.
- Experience deploying and scaling agentic workloads on AWS, Azure, or GCP.
- Experience with vector databases such as Pinecone, Weaviate, FAISS, Elastic, or MongoDB Atlas Vector Search.
- Strong fundamentals in data structures, algorithms, system design, and distributed application architecture.
- Experience designing and consuming RESTful and event‑driven APIs for AI system integration.
- Knowledge of containerization, CI/CD pipelines, and production deployment best practices for AI systems.
- Ability to collaborate with team members effectively with both technical and non‑technical stakeholders.

Preferred / Valuable to Have:

- Experience building autonomous or semi‑autonomous agents for workflow automation, decision support, or internal tooling.
- Familiarity with agent evaluation and observability tools.
- Understanding of guardrails, safety frameworks, and governance in enterprise AI systems.
- Exposure to knowledge graphs, symbolic reasoning, or graph‑based agent memory systems.
- Contributions to open‑source AI, LLM, or agentic frameworks.

Basic Qualifications

- Bachelor's or Master's degree in Engineering, Computer Science, AI, or a related field.
- 4+ years of industry experience, focused on LLM‑based systems, RAG, or Agentic AI.
- Strong communication skills and the ability to work in cross‑functional, fast‑moving teams.

📌 Gen AI Developer (India)
🏢 Sparix Global
📍 India