AI ML Developer

Key Responsibilities

• Design and develop backend microservices using FastAPI / Uvicorn, following SOLID principles and modular design.
• Implement and optimize AI workflows including RAG / Graph RAG pipelines, Neo4j knowledge graphs, and LLM-based agents for test generation and analysis.
• Integrate multi-model orchestration (OpenAI, Anthropic, Azure AI, Gemini, Claude) with dynamic model selection and token efficiency.
• Enhance context management modules supporting multiple data sources (Confluence, SharePoint, Excel, PDFs, Images, and APIs).
• Develop and maintain test generation, regeneration, and automation script creation pipelines.
• Implement observability and telemetry for model performance, API throughput, and agentic decision tracking.
• Collaborate with product architects and data scientists to improve model determinism, reduce hallucination, and ensure explainable outputs.
• Contribute to DevOps pipelines (Azure DevOps / AWS Code Pipeline) for build, test, and deploy automation.

Key Skills & Experience

• 3–8 years of experience in Python-based full-stack / backend development (FastAPI, Flask, Django). (3-5 Engineers & 5-8 Sr Engineers)
• Solid understanding of AI/ML fundamentals, especially in prompt engineering, LLM APIs, vector databases (Chroma / FAISS / OpenSearch), and Graph Databases (Neo4j).
• Experience implementing microservices, REST APIs, and async I/O architectures.
• Proficiency in CI/CD, containerization (Docker / Podman), and cloud deployments (Azure / AWS).
• Experience with test frameworks (PyTest, Robot, Playwright, Selenium).
• Exposure to RAG architectures, embedding models, and LangChain / LangGraph frameworks preferred.
• Knowledge of data security, API governance, and model observability is an advantage.

Behavioral Attributes

• Passionate about AI-driven innovation in QE.
• Strong analytical and problem-solving mindset.
• Self-driven, adaptable to emerging tools and technologies.
• Comfortable working in an agile, cross-functional environment.

Education:

• B.Tech / M.Tech / MCA or equivalent degree in Computer Science or related field.
• Certifications in AI/ML, Cloud (Azure/AWS), or Testing Tools preferred.

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