Role Overview :

We are looking for a Senior AI Engineer to design, build, and deploy AI-powered systems and solutions.

You will work closely with the AI Engineering leadership to develop intelligent features, integrate large language models (LLMs) into products, and build scalable AI infrastructure.

This role requires a strong hands-on engineer who thrives at the intersection of applied machine learning, software engineering, and Generative AI.

Key Responsibilities :

Design and Build AI Systems :

- Design, develop, and deploy production-ready AI/ML solutions, including LLM-powered features, classification models, and recommendation systems.

- Build and optimize RAG (Retrieval-Augmented Generation) pipelines for knowledge-intensive applications.

- Develop and maintain agent-based AI systems for task automation and intelligent workflows.

LLM Integration and Prompt Engineering :

- Integrate and fine-tune large language models (GPT, Claude, Llama, Mistral) for domain-specific use cases.

- Design effective prompting strategies, including chain-of-thought, few-shot, and system prompts.

- Evaluate and benchmark LLM performance across accuracy, latency, and cost dimensions.

Infrastructure and Scalability :

- Build scalable AI serving infrastructure using containerized microservices and cloud-native patterns.

- Implement vector database solutions (Pinecone, Weaviate, Qdrant, pgvector) for semantic search and retrieval.

- Set up monitoring, logging, and alerting for AI systems in production.

Collaboration and Best Practices :

- Partner with product and business teams to translate requirements into technical AI solutions.

- Contribute to code reviews, architectural discussions, and documentation.

- Stay current with the latest AI research and evaluate new tools, models, and techniques for adoption.

Required Experience :

- 5+ years of experience in software engineering, with strong programming fundamentals and system design skills.

- 1 - 2 years of hands-on experience working with LLMs and Generative AI in real-world or production settings.

- Strong proficiency in Python and experience with AI/ML frameworks (PyTorch, TensorFlow, scikit-learn).

- Practical experience with vector databases, embeddings, and RAG architectures.

- Familiarity with agent-based systems and multi-step AI workflows (LangChain, LlamaIndex, CrewAI, or similar).

- Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

- Strong software engineering fundamentals - clean code, testing, version control, CI/CD.

- Background in classical ML or NLP is a strong plus - candidates who transitioned from traditional ML into GenAI are especially valued.

Preferred Qualifications :

- Experience in the fintech or financial services domain.

- Familiarity with AIOps tools and practices - model versioning, experiment tracking, drift monitoring.

- Experience with fine-tuning open-source LLMs and managing model inference at scale.

- Contributions to open-source AI/ML projects or published work.

- Bachelor's or Master's degree in Computer Science, AI/ML, or a related field