Software Engineer – Generative AI & Agentic Systems

Job Title: Software Engineer Generative AI & Agentic Systems

Experience: 5+ Years

Location: Hyderabad

Employment Type: Full-Time

About the Role

We are seeking a highly skilled Software Engineer with strong expertise in Generative AI (GenAI) and Agentic AI architectures to design and build intelligent, AI-driven solutions embedded across the Software Development Life Cycle (SDLC) .

In this role, you will develop autonomous and semi-autonomous agents , Retrieval-Augmented Generation (RAG) pipelines, and AI-powered workflows that enhance developer productivity, automation, and decision-making across engineering platforms. You will work closely with product, architecture, DevOps, and platform engineering teams to integrate GenAI capabilities into CI/CD pipelines and enterprise systems.

Key Responsibilities

GenAI & Agentic Solution Development

• Design, develop, and deploy GenAI-powered applications and agentic workflows integrated into SDLC tools and engineering platforms.
• Build intelligent agents capable of reasoning, planning, and executing tasks across development and operational workflows.
• Implement orchestration patterns for multi-agent and tool-using AI systems .

RAG & Knowledge Systems

• Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise-scale use cases.
• Integrate vector databases to enable semantic search, contextual grounding, and knowledge retrieval.
• Optimize embedding strategies and retrieval techniques for accuracy, performance, and scalability.

Backend & Platform Engineering

• Develop APIs, microservices, and integration layers that enable AI-driven automation.
• Build scalable, secure backend services to support GenAI workloads.
• Integrate AI services with internal platforms, developer tools, and enterprise systems.

SDLC & DevOps Integration

• Collaborate with DevOps and platform teams to embed AI capabilities into CI/CD pipelines .
• Automate code reviews, testing, documentation, and deployment workflows using AI agents.
• Ensure AI-driven workflows align with SDLC best practices and engineering standards.

Cloud, Security & Compliance

• Deploy and operate GenAI solutions on cloud platforms (AWS, Azure, or GCP) .
• Containerize AI services using Docker and orchestrate them with Kubernetes .
• Ensure compliance with security, privacy, and ethical AI standards , including data protection and access control.

Observability & Performance (Plus)

• Implement observability agents for monitoring AI workflows, model performance, latency, and failures.
• Continuously improve system reliability, scalability, and cost efficiency.

Required Skills & Qualifications

Core Engineering Skills

• 5+ years of professional software engineering experience.
• Strong programming skills in Python, Java, or TypeScript .
• Solid understanding of system design, APIs, and microservices architecture .

Generative AI & Agentic AI

• Hands-on experience with LLM frameworks such as OpenAI, Hugging Face, LangChain , or similar.
• Strong understanding of Agentic AI architectures , orchestration frameworks, and tool-based reasoning.
• Expertise in prompt engineering , LLM evaluation, and optimization techniques.

RAG & Vector Databases

• Proven experience implementing RAG architectures .
• Hands-on experience with vector databases such as Pinecone, Weaviate, Milvus , or equivalent.
• Knowledge of embedding models and semantic search techniques.

Cloud & DevOps

• Experience with cloud platforms (Azure, AWS, or GCP).
• Hands-on experience with Docker and Kubernetes .
• Understanding of CI/CD pipelines, DevOps automation , and SDLC best practices.

Nice-to-Have / Plus Skills

• Experience with observability and monitoring tools for AI workflows.
• Exposure to model fine-tuning, evaluation frameworks, and ML lifecycle management.
• Experience with event-driven architectures and messaging systems.
• Familiarity with governance frameworks for responsible and ethical AI.

Soft Skills

• Strong problem-solving and analytical thinking skills.
• Excellent communication and cross-functional collaboration abilities.
• Ability to translate complex requirements into scalable technical solutions.
• Passion for innovation and continuous learning in the AI/ML space.