AI Senior Engineer

AI Senior Engineer

About the Role:

We are looking for a highly capable AI Lead Engineer to contribute to the design and delivery of intelligent, scalable AI solutions. This role focuses on building production-grade systems involving LLMs, vector databases, agent-based workflows, and Retrieval-Augmented Generation (RAG) architectures on the cloud. The ideal candidate should demonstrate strong problem-solving abilities, hands-on technical skills, and the ability to align AI design with real-world business needs.

Must-Have Skills

• Strong coding ability in Python and proficiency in SQL.
• Hands-on experience with vector databases (e.g., Pinecone, FAISS, Weaviate).
• Practical experience with LLMs (OpenAI, Claude, Gemini, etc.) in real-world workflows.
• Familiarity with LangChain, LlamaIndex, or similar orchestration tools.
• Proven track record in delivering scalable AI systems on public cloud (Azure, AWS, or GCP).
• Experience building and optimizing RAG pipelines.
• Solid understanding of server less/cloud-native architecture and event-driven design.
• Integrate/expose the ai solution in applications using fastapi,flask,django

Preferred or Good to Have Skills

• Exposure to agentic AI patterns and multi-agent coordination.
• Knowledge of AI system safety practices (e.g., hallucination filtering, grounding).
• Experience with MLOps tools (MLflow, KubeFlow) and CI/CD for ML.
• Understanding of concept/data drift and retraining strategies in production.
• Experience working on AI projects involving classification, regression, and clustering models.
• Prior work on multi-modal AI pipelines (vision + language).
• Familiarity with real-time inference tuning (batching, concurrency).
• Demonstrated ability to deliver a variety of AI solutions in production environments across domains.

Any Other:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
• Strong analytical mindset with a clear focus on business-aligned AI delivery.
• Excellent verbal and written communication skills.

Key Responsibilities

• Collaborate with the Solution Architect to design agentic AI systems (e.g., ReAct, CodeAct, Self-Reflective Agents).
• Build and deploy scalable RAG pipelines using vector databases and embedding models.
• Integrate modern AI tools (e.g., LangChain, LlamaIndex, Kagi, Search APIs) into solution workflows.
• Optimize inference performance for cloud and edge environments.
• Contribute to the development of feedback loops, drift detection, and self-healing AI systems.
• Deploy, monitor, and manage AI solutions on cloud platforms (Azure, AWS, or GCP).
• Translate business use cases into robust technical solutions in collaboration with cross-functional teams.