Role: Data Science & Machine Learning - Other
Industry Type: IT Services & Consulting
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Data Science & Machine Learning
UG: Graduation Not Required
About the Role : We are building a high-impact AI Reliability and Evaluation practice focused on enterprise AI systems for the Banking and Financial Services (BFSI) domain. We are looking for highly capable engineers who can independently design, implement, and operationalize evaluation frameworks for LLMs, AI agents, RAG systems, and enterprise AI workflows. This role is ideal for candidates who combine strong engineering fundamentals with an analytical mindset and a passion for building trustworthy AI systems. You will work closely with enterprise customers, AI architects, data scientists, and product teams to ensure AI systems are measurable, reliable, safe, and production-ready.
Key Responsibilities
Design and implement evaluation frameworks for LLM applications, AI agents, RAG pipelines, and conversational AI systems. Develop automated evaluation pipelines for hallucination detection, faithfulness, relevance, safety, and robustness. Build benchmark datasets and golden evaluation sets for BFSI use cases. Define measurable AI quality KPIs and SLAs for enterprise deployments. Build and test AI agents using LangChain, LangGraph, CrewAI, AutoGen, and related frameworks. Implement observability pipelines using Arize Phoenix, LangSmith, TruLens, MLflow, and OpenTelemetry. Work directly with enterprise banking customers and stakeholders. Present findings, recommendations, and reliability reports to technical and business teams.
Required Skills
& Qualifications Strong hands-on experience in Python, APIs, LLM application development, prompt engineering, RAG architectures, and vector databases. Experience with OpenAI APIs, Anthropic Claude, Gemini APIs, Hugging Face, LangChain, and LangGraph.. Good understanding of AI safety, guardrails, agentic workflows, and benchmarking methodologies. Exposure to AI evaluation and observability tools such as Arize Phoenix, LangSmith, DeepEval, Ragas, TruLens, and MLflow. Immediate joiners strongly preferred. Academic Requirements B.Tech / M.Tech / BE / MS in Computer Science, AI/ML, Data Science, Electronics, or related disciplines. Strong preference for candidates from premium institutions such as IITs, NITs, BITS, IIITs, and top engineering institutes. Consistently strong academic performance and GPA preferred. What WeÆre Looking For Independent thinkers who can own problems end-to-end. Agile engineers comfortable working in fast-moving environments. Strong communication and stakeholder management skills. Candidates passionate about trustworthy and measurable AI systems. Preferred Candidate Profile Experience building production-grade AI agents and evaluation pipelines. Exposure to BFSI or regulated enterprise environments. Contributions to open-source AI tooling or AI reliability initiatives. Certifications in Arize or related AI observability/evaluation platforms are a strong plus. Why Join Us Work on cutting-edge enterprise AI reliability challenges. Exposure to large BFSI customers and real-world AI deployments. Significant ownership, visibility, and rapid career growth opportunities. Opportunity to become a core contributor in a fast-growing AI Reliability business unit