Job description

We are seeking a skilled Generative AI Engineer to join our team where you will harness model capabilities to implement cutting-edge algorithms and solutions across myriad industries.

You will serve as a pivotal link between Data Scientists, ML and Platform Engineers to unleash the potential of Generative AI technology by implementing business-centric solutions. You will help customers find the appropriate level of refinement among semantic search, RAG, agents, and ultimately fine-tuning to reach their value delivery threshold in the most cost-effective way.

Beyond crafting prompts, you will be responsible for designing and building robust and scalable products starting with benchmarks of candidate FMs through targeted requests, rapidly iterating prototypes, and validating product ideas. Your expertise in orchestrating the entire AI workflow will ensure the seamless integration of advanced models' capabilities into applications, optimizing performance, security, compliance, scalability, and efficiency. You will competently navigate between prompts, chains, and agents while mastering the underlying infrastructure challenges.

We invest in your success through comprehensive training, combining internal programs with resources from our technology partners.

Join us if you are passionate about pushing the boundaries of AI technology and making a significant impact in enabling our customers to create GenAI-powered applications with confidence and a fast time to market.

Key Responsibilities

You are part of a cross-functional consulting team that drives the adoption of Generative AI in every imaginable sector, working step-by-step with customers to understand business requirements to design then build bespoke GenAI solutions.

• Build applications powered by LLMs (OpenAI, Claude, Mistral, etc.) using LangChain, LlamaIndex, and related GenAI frameworks.
• Implement RAG pipelines with vector DBs (Pinecone, FAISS, pgvector, ChromaDB) for grounding LLM responses with internal knowledge
• Develop multimodal AI solutions (text, audio, image) and build autonomous agents where relevant.
• Drive MLOps excellence: CI/CD (ML pipelines), drift detection, canary releases, retraining schedules.
• Design robust and reusable prompt templates using CoT, ReAct, Graph-of-Thought, and Agent flows.
• Continuously improve model reliability, relevance, and UX by tuning prompt flows
• Deploy GenAI models on AWS/GCP/Azure using services like SageMaker, Bedrock, Vertex AI
• Ensure performance observability, security guardrails, and compliance (GDPR, Responsible AI)
• Work with DevOps teams to integrate GenAI solutions into microservices and APIs (FastAPI/Flask)
• Benchmark open-source and commercial LLMs for use-case fit and cost-performance tradeoffs
• Evaluate fine-tuning strategies (PEFT, LoRA, RLHF) where applicable for proprietary use cases
• Support solution architects and cross-functional teams in delivering PoCs and enterprise-grade rollouts
• Document frameworks, best practices, risks, and learnings for future scaling