Senior AI Engineer/Lead

Senior AI Engineer/Lead

Key Responsibilities

Engineering Production Grade Development

• Handson Coding Lead the development of production ready systems with expert level proficiency in Python or PySpark
• Solution Engineering Apply advanced data structures algorithms and software design patterns to solve real world financial services challenges
• Scalability Performance Architect high scale solutions with a big picture approach ensuring system latency and infrastructure costs are optimized to drive tangible business value
• Lifecycle Management Own the transition from MVP to live solutions managing change control and enterprise level AI integration

Advanced AI Implementation RD

• Generative AI RAG Design and deploy sophisticated RAG pipelines and Transformer based architecture Orchestrate LLMasaService eg GPT4 Gemini Vertex AI alongside local SLMs eg Llama 3 Mixtral
• Agentic Workflows Build autonomous agents using frameworks such as LangGraph preferred CrewAI or AutoGen to automate complex multistep business logic
• MLOps Governance Take full ownership of the model lifecycle including finetuning LLMSLM monitoring model drift groundtruth validation and ensuring compliance with Model Risk Management MRM standards
• UAT Validation Drive User Acceptance Testing UAT focused on specific business outcomes and accuracy benchmarks

Leadership Solution Orchestration

• Stakeholder Management Navigate complex client ecosystems acting as the primary technical liaison for both Csuite stakeholders and engineering teams
• Strategic Communication Translate high level business requirements into sustainable high value generative AI solutions
• CoE Liaison Partner with the BFS AI CoE to bring cutting edge RD and incubated solutions and active participation for multiple client AI solutions demo and delivery assurance to global clients
• Team Mentorship Lead and inspire a high performing technical team fostering a positive solution mind and an initiative taking culture

Technical Qualifications

Education

• bachelors or masters degree in computer science Engineering or a related quantitative field

Experience

• 10 years Enterprise Application development Proven track record of delivering AIML solutions in a production environment specifically within the BFSI or highly regulated sectors
• Tooling Deep expertise in Python LangGraphLangChain Vector Databases and cloudnative AI stacks Azure AI AWS Bedrock or GCP Vertex AI
• Architecture Strong foundation in microservices API design and enterprise security protocols

Skills

• Mandatory Skills : GenAI - LLMOps
• Good to Have Skills : Python