We Are Hiring: Senior AI & ML Engineer

Location: Hyderabad

Experience: 4 - 8 years

Candidates from Tier-1 institutes will be preferred

We are looking for a highly hands-on Senior AI & ML Engineer with strong experience in building and deploying production-grade Generative AI and Agentic AI solutions. This is a coding-intensive role requiring expertise in custom AI solution development, semantic layers, cloud-based AI services and collaboration with complex stakeholder groups.

Key responsibilities:

- Design, develop and deploy Generative AI and Agentic AI applications from concept to production.
- Build multi-step and multi-agent workflows using LangChain, LangGraph, Semantic Kernel, AutoGen or similar frameworks.
- Develop custom AI applications, orchestration components, APIs, tools and reusable Python modules.
- Build production-grade Retrieval-Augmented Generation solutions using embeddings, vector databases, hybrid search and re-ranking.
- Design AI agents capable of reasoning, planning, tool calling, memory management and workflow execution.
- Contribute to semantic-layer design by defining business entities, relationships, metadata and contextual mappings across complex data landscapes.
- Support knowledge graphs, semantic search, enterprise-data pipelines and AI governance initiatives.
- Implement appropriate guardrails, evaluation frameworks, monitoring and human-in-the-loop controls.
- Collaborate with architects to build scalable, secure and enterprise-ready AI solutions.
- Review code, mentor fellow engineers and promote engineering excellence.
- Partner with business and technology teams to translate complex requirements into working AI solutions.

Mandatory technical skills:

- 4 years of software engineering or AI/ML engineering experience.
- Proven hands-on experience delivering GenAI or Agentic AI solutions to production.




- Robust Python coding and backend/API development skills.
- Hands-on experience building custom AI solutions.
- Strong experience with Agentic AI concepts, including multi-agent architecture, agent orchestration, planning, reasoning, tool calling, agent state/memory, human-in-the-loop workflows, guardrails and agent evaluation.
- Practical experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI or similar frameworks.
- Strong experience with LLMs, prompt engineering, RAG, embeddings, vector databases and semantic/hybrid search.
- Experience taking AI applications through development, testing, deployment and production monitoring.

Practical cloud experience, preferably on Microsoft Azure:

- Azure OpenAI, Azure AI Foundry/AI Studio, Azure AI Search, Azure Machine Learning.
- Azure App Service, Functions or container services.
- Experience with Docker, Kubernetes, CI/CD and cloud-native deployment practices.

Semantic-layer expectations:

- Practical experience in designing semantic models, defining business entities/relationships, building metadata-driven AI solutions, working with knowledge graphs/ontologies, and connecting structured/unstructured data.

Stakeholder-management expectations:

- Experience working in a complex, multi-stakeholder environment (Business, Architects, Data/AI teams, InfoSec).
- Ability to convert complex business requirements into technical AI solutions, manage conflicting priorities, and influence technical decisions.

Preferred qualifications:

- Experience mentoring engineers, conducting code reviews or leading technical projects.
- Knowledge of LLMOps, model evaluation, prompt/version management and production monitoring.
- Experience with knowledge graphs and enterprise data pipelines.
- Azure AI or Azure Data certifications.
- Exposure to financial services, investment management, banking or other regulated industries.

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