AI Engineer

We are looking for an experienced AI Engineer to join our AI engineering team in Hyderabad. The team is new and built around strong early-career engineers - what it needs now is senior craft alongside them.

Our goal is to automate expert work for two audiences. Internally, we build AI systems that let teams across the company produce more and better work in less time. Externally, we build custom AI solutions for enterprise customers - bespoke enrichment pipelines, data feeds, and automated workflows shaped around a specific customers problem. The internal tools we build usually become the foundation of what we sell.

AI engineers and software engineers build and jointly own our solutions. You will work alongside them from problem framing and prototyping through production and iteration, and help set the engineering bar for a team that is still forming it.

What Youll Do

Build and ship AI systems

• Design, build, and operate LLM-powered agents and multi-step workflows - tool use, planning, state and memory, human-in-the-loop checkpoints, and sensible recovery when a step fails.
• Build forward-engineering agents: systems that take an ambiguous customer or business input and produce working technical output - queries, configurations, enrichment logic, briefs - that internal teams and customers then rely on.
• Take solutions into production and keep them healthy - deploy, monitor, and optimize for reliability and cost together.

Get the quality right

• Do prompt engineering properly: task decomposition, context design, structured outputs, tools and schemas, and the right model for each step. We treat prompts as engineering artifacts - versioned and reviewed like code.
• Build evaluation into the work - golden datasets, regression suites, and the metrics that matter for each workflow: accuracy, groundedness, hallucination rate, latency, and cost per unit of work.
• Know when an LLM is not the answer, and when retrieval, a classical model, or plain deterministic code is better.

Lift the team

• Mentor early-career engineers through code review, pairing, and design discussion. Most of the team is within a year of graduating and learns fast when it is taught well.
• Help set the standards the team works to - testing, prompt and evaluation conventions, observability, and what done means for an AI feature.
• Work with product managers, platform engineers, and the teams who use what we build, across several time zones - translating fuzzy requirements into a technical approach with the trade-offs stated plainly.

What Youll Bring

• 4-9 years in software engineering, AI/ML engineering, or a related technical role, including hands-on experience taking AI-powered applications into production.
• A system you have built and operated where an LLM did real work - and a clear sense of how you knew it was working, what broke, and what you changed.
• Strong Python and solid software engineering fundamentals, with a good understanding of API design and integration patterns.
• Practical experience with agent and orchestration frameworks (LangChain, LangGraph, MCP-based tooling, or equivalent) and with frontier model APIs (Anthropic, OpenAI, or comparable).
• Working knowledge of RAG, vector and keyword search (OpenSearch, Elasticsearch, or equivalent) for grounding models in proprietary data.
• A solid grounding in traditional ML alongside the generative side - classification, clustering, embeddings, feature engineering, and standard evaluation methodology - and the judgment to pick a classical model when it is faster, cheaper, and more predictable than a prompt.
• Experience with at least one major cloud (AWS, Azure, or Google Cloud), containers, and CI/CD.
• Some experience mentoring or technically guiding less-experienced engineers.
• Clear communication and comfort with ambiguity - a working prototype that proves the idea, then the engineering to make it durable.
• Bachelors or Masters in Computer Science or an equivalent degree.

Nice to Have

• Large-scale LLM enrichment or classification pipelines, where cost and quality per document both matter.
• A background in NLP, information retrieval, or media and text analytics.
• Transformers, fine-tuning, PyTorch or TensorFlow; or computer vision and speech-to-text in production.

Why This Role

The team is new, the problem space is genuinely unsolved, and the work goes straight into the hands of people who depend on it daily. You will shape how a team …