Senior Full Stack GenAI Engineer

Required Education

• Bachelor's Degree.

• 10+ years of software engineering and development experience
• Proven experience in building and deploying GenAI applications in production.
• Strong programming skills in Python / JAVA and familiarity with GenAI libraries (Transformers, Lang Chain, Hugging Face, etc.).
• Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with CI / CD for ML workflows and versioning tools like MLflow or DVC.
• Knowledge of prompt engineering, few-shot learning, and agent-based systems.
• Hands‑on experience designing and building cloud‑native solutions (preferably on AWS)
• Experience with modern architecture styles : microservices, APIs, event‑driven systems
• Strong ability to articulate technical solutions, trade‑offs, and system behavior to both technical and non‑technical stakeholders

• Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, Lang Chain, Bedrock)
• Familiarity with AWS AI / ML services (e.g., Sage Maker, Bedrock, Comprehend, Lex)
• AWS AI certification
• Financial Services experience

• Senior GenAI Engineer Initiatives to drive the design of secure, scalable, and modern applications, with a strong emphasis on AI and GenAI‑enabling technologies. This is a senior‑level individual contributor role within the Architecture organization, focused on delivering hands‑on solution designs and proofs of concept that bring innovative ideas to life. You will work closely with Domain Architects, product teams, and engineers to solve real business problems by developing good scalable GenAI Solutions.
• Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval‑augmented generation (RAG).
• Fine‑tune foundation models using domain‑specific data.
• Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).
• Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.
• Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.
• Monitor and optimize model performance, latency, and cost.
• Use techniques like quantization, distillation, and caching to improve efficiency.
• Stay ahead of GenAI trends and emerging technologies.
• Drive experimentation with new models, agents, and frameworks (e.g., Lang Chain, Llama Index, OpenAI, Anthropic, etc.).
• Ensure compliance with data privacy, security, and regulatory standards.
• Evaluate and select appropriate model types (open‑source vs proprietary) based on business needs.
• Lead hands‑on solution evaluations, prototypes, and proofs of concept, especially for initiatives involving AI, GenAI, and emerging technologies.
• Make informed architectural trade‑offs based on business needs, performance, cost, and long‑term maintainability.
• Contribute reusable patterns and documentation that support solution delivery across teams.
• Stay informed on trends in cloud services, architecture frameworks, and GenAI tooling.
• Full Stack 5 years – Java / Python, CI / C pipelines must
• At least 2 years should be with Gen AI tools and framework.
• AWS - Must

Only those lawfully authorized to work in the designated country associated with the position will be considered.

Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.