Software Engineer - AI Engineering

Job highlights

• Anblicks is a Great Place to Work Certified Data and AI company that enables enterprises to become intelligent,data-driven organizations
• Experience: 4+ Years. Job Type: Full-Time. About Anblicks
• We are looking for a Software Engineer - AI Engineering with strong full-stack development skills and hands-on experience building AI-powered applications

Job Title: Software Engineer - AI Engineering

Location: Hyderabad, India

Experience: 4+ Years

Job Type: Full-Time

About Anblicks

Anblicks is a Great Place to Work Certified Data and AI company that enables enterprises to become intelligent, data-driven organizations. We specialize in Data Engineering, Cloud, Analytics, and AI solutions, helping global businesses accelerate innovation and digital transformation.

Position Overview

We are looking for a Software Engineer - AI Engineering with strong full-stack development skills and hands-on experience building AI-powered applications. You will contribute to developing enterprise-grade AI platforms, intelligent agents, and LLM-powered solutions using technologies such as Python, TypeScript, APIs, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and vector databases.

This is a hands-on software engineering role focused on building production-ready AI applications-not a traditional Machine Learning or Data Science position. You will work across frontend, backend, AI integrations, and data pipelines to deliver secure, scalable, and reliable AI solutions.

Key Responsibilities

• Develop and maintain full-stack applications, including user interfaces, backend services, REST APIs, and LLM integrations.
• Build AI agent workflows using LLMs, prompt engineering, tool/function calling, and structured outputs.
• Develop and integrate Model Context Protocol (MCP) servers to connect AI agents with enterprise tools, APIs, and data sources.
• Design and enhance RAG pipelines, including data ingestion, chunking, embeddings, vector search, and context retrieval.
• Build secure AI platform capabilities, including access controls, policy enforcement, human approvals, and usage monitoring.
• Integrate enterprise data sources, semantic layers, business glossaries, and knowledge graphs into AI workflows.
• Develop and maintain data pipelines that support AI applications and RAG-based solutions.
• Implement automated testing, LLM evaluations, logging, tracing, and monitoring to ensure application quality and reliability.
• Follow security and privacy best practices, including PII protection, authentication, authorization, and secrets management.
• Collaborate with AI engineers, data engineers, and product teams to deliver scalable solutions.
• Document technical components, troubleshoot production issues, and contribute to reusable libraries and engineering best practices.

Required Qualifications

• Bachelors degree in Computer Science, Software Engineering, or a related discipline, or equivalent practical experience.
• 4+ years of professional software engineering experience, with strong backend and full-stack development capabilities.
• Proficiency in Python and/or TypeScript/JavaScript with Node.js.
• Experience developing user-facing applications using React, Next.js, or similar frontend frameworks.
• Strong understanding of REST APIs, backend services, and application integration.
• Hands-on experience with LLM APIs such as OpenAI, Anthropic Claude, or Google Gemini, including prompt engineering and tool/function calling.
• Working knowledge of RAG architectures, embedding models, vector databases, and frameworks such as LangChain, LangGraph, or LlamaIndex.
• Experience with SQL, data pipelines, and data platforms such as Snowflake, Databricks, or dbt.
• Familiarity with Git, CI/CD pipelines, Docker, and cloud platforms such as AWS, Azure, or GCP.
• Experience using AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, or Windsurf.
• Strong analytical, problem-solving, communication, and collaboration skills.

Good to Have

• Experience with MCP and agent development frameworks such as OpenAI Agents SDK, Claude Agent SDK, CrewAI, or AutoGen.
• Exposure to knowledge graphs, ontologies, and semantic technologies such as Neo4j, RDF/SPARQL, or Snowflake Semantic Views.
• Familiarity with LLM evaluation and observability tools such as LangSmith, Langfuse, or Ragas.
• Understanding of authentication and authorization standards, including OAuth 2.0 a…