AI Engineer

Key Responsibilities:

Software Engineering & System Design

· Write, test, and deployproduction-quality code with a strong focus on scalability and performance.

· Design and implementend-to-end systems including API, database, and application layers.

· Considermemory usage, performance optimization, and modular architecture in code design.

· Follow modernDevOps practices for deployment and environment management.

Python Development

· Write clean, modular Python code with proper environment management (virtualenv, poetry, conda).

· Build and deployRESTful APIs using frameworks likeFastAPI or Flask.

· Connect applications to relational and NoSQL databases.

· Containerize applications usingDocker and deploy inKubernetes / cloud environments.

Database Skills

· Write and optimizeSQL and PL/SQL queries for data retrieval and transformation.

· Integrate database logic effectively into application workflows.

Generative AI Development

· Understand howLarge Language Models (LLMs) work — architecture, limitations, and tuning methods.

· Design and implementRAG (Retrieval-Augmented Generation) systems:

o Build pipelines connecting vector databases, LLMs, and application layers.

o Optimize retrieval and response accuracy throughprompt engineering andcontext management.

o Applybest practices andadvanced RAG techniques (chunking strategies, caching, query re-ranking).

· Develop and manageprompt templates, parameter configurations, and evaluation metrics.

Agentic AI Systems

· UnderstandAI agents, their lifecycle, and how they integrate with tools and APIs.

· Implementtool calling andhuman-in-the-loop workflows.

· Designmulti-agent architectures using frameworks such asLangChain orLangGraph.

· Applyagent orchestration best practices, ensuring reliability, observability, and control.

Required Skills & Qualifications

· Strong understanding ofsoftware design principles and ability to think like a developer (language agnostic).

· Proficiency inPython with good exposure to building APIs, database integration, and container-based deployment.

· Working knowledge ofSQL / PL-SQL for querying and joining data.

· Experience in developing or integratingGenAI or RAG-based systems using OpenAI, Anthropic, or similar models.

· Familiarity withLangChain,LangGraph, or similar frameworks for AI workflow orchestration.

· Strong debugging, optimization, and analytical skills.

· Excellent communication and collaboration abilities in a fast-paced environment.

Nice to Have

· Exposure tocloud platforms (AWS, GCP, Azure) for AI workload deployment.

· Experience withvector databases (FAISS, Pinecone, Weaviate, or Chroma).

· Knowledge ofmonitoring and observability tools for AI systems.

· Familiarity withCI/CD pipelines,GitOps, andinfrastructure automation.