GenAI Platform Data Engr

deploy production-grade Generative AI solutions (RAG pipelines, conversational assistants, multi-agent systems) using Python and modern LLM frameworks. * Lead prompt engineering, chain-of-thought orchestration, structured output parsing, guardrails and evaluation pipelines for LLM-based applications. * Architect and own RAG pipelines end-to-end: document ingestion, chunking, embeddings, vector store management and retrieval optimization. Platform & MLOps * Deploy and operate GenAI applications on cloud infrastructure (AWS, Azure or GCP), with a focus on scalability, security and cost optimization. * Implement evaluation and monitoring frameworks for AI systems: response quality, latency, hallucination detection and feedback loops. * Define MLOps practices for LLM-based systems: versioning, automated evaluation and production monitoring. Leadership & Stakeholder Management * Act as technical lead for GenAI initiatives, mentoring engineers and setting technical direction. *

Translate business requirements from banking stakeholders (risk, compliance, customer experience) into robust technical solutions. * Partner with architecture, security and compliance teams to ensure GenAI solutions meet the regulatory standards of the banking sector. REQUIRED SKILLS & EXPERIENCE * 5+ years of experience in software engineering, with significant hands-on experience building Generative AI / LLM-based solutions in production. * Expert-level Python skills, including experience with modern GenAI frameworks (LangChain, LlamaIndex or equivalent). * Deep understanding of LLM concepts: RAG architectures, embeddings, prompt engineering, fine-tuning and evaluation methodologies. * Hands-on experience integrating LLM providers (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) into production systems. * Experience with vector databases (Pinecone, OpenSearch, FAISS, Weaviate) and embedding optimization. * Solid cloud experience (AWS, Azure or GCP) for deploying and scaling AI workloads. * Strong understanding of data security, privacy and regulatory considerations relevant to the banking / financial sector. * Proven ability to lead technical initiatives and mentor engineering teams. * Fluent English. NICE TO HAVE * Experience designing multi-agent or agentic AI workflows. * Familiarity with AI observability tools (Langfuse, Weights & Biases, Helicone). * Prior experience in banking, financial services or other highly regulated industries. * Experience with MLOps practices and model governance frameworks. EDUCATION * Degree in Computer Science, Software Engineering, AI/ML or a related field. PREFERRED CERTIFICATIONS * AWS, Azure or GCP ML/AI certifications, a plus. WORKING MODEL Fully remote position. Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national

As a Senior / Lead GenAI Engineer, you will design, build and scale production-grade Generative AI solutions for a leading company in the banking sector, taking technical ownership from architecture through deployment, in a fully remote role. Don’t tick every box? If you meet around 70% of the requirements above, we’d still encourage you to apply. ABOUT THE ROLE We are looking for a Senior / Lead GenAI Engineer with deep, hands-on expertise in Python and Large Language Models to design, build and scale Generative AI solutions for a leading banking sector client. In this role, you will take technical ownership of GenAI initiatives end-to-end - from architecture and prototyping through to secure, compliant production deployment - while mentoring engineers and partnering with business, risk and compliance stakeholders to ensure solutions meet the standards of a highly regulated environment. KEY RESPONSIBILITIES GenAI Solution Design & Delivery * Design, build and