Live opening · Posted 8 days ago

AI Solutions Engineer

Dautom · India (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 8 days ago
CompanyDautom
LocationIndia (Remote)
Work modeYes
SkillsPython, TypeScript, React, Azure, Docker, Kubernetes, Terraform
SourceLinkedin
ListedPosted 8 days ago

About the role

Description supplied by the original job listing.

In this role, you will collaborate closely with one of our esteemed clients—a globally recognized leader in their industry, distinguished by their commitment to excellence, innovation, and delivering exceptional value. As a trusted IT consulting partner, Dautom is supporting their strategic initiatives by connecting them with exceptional talent to drive business growth and transformation.
About the Role :
Job Title: AI Solutions Engineer
Job Type: 1year + extendable long term contract
Remote from India
We are looking for a hands-on AI Solutions Engineer who can take generative and agentic AI solutions from design to production. You will own the full stack: LLM orchestration, retrieval, backend services, user interface, deployment, and evaluation. This is an engineering role first. You will write production code every day and be accountable for the reliability, security, and cost of what you ship.
Key Responsibilities :
• Architect and build multi-agent systems with stateful orchestration, tool calling, routing, memory, and human-in-the-loop checkpoints
• Design retrieval pipelines covering document parsing, chunking, embeddings, hybrid search, and reranking, grounded in governed enterprise data
• Build high-performance Python backend services and streaming APIs that expose agents to web, chat, and voice channels
• Develop responsive React and TypeScript front ends with real-time streaming, rich visualizations, and clean UX for business users
• Deploy and operate AI workloads on the lakehouse platform and cloud, using containers, CI/CD, and infrastructure as code
• Implement LLMOps practices: offline and online evaluation, LLM-as-judge scoring, tracing, prompt versioning, and regression testing
• Engineer guardrails for prompt-injection defense, PII protection, output validation, and role-based data access
• Optimize latency, token cost, and throughput through model selection, caching, prompt design, and parallel execution
• Translate business requirements into technical designs, and document architecture decisions for review
• Mentor engineers and contribute reusable components, templates, and standards to the wider team
Technical Skills Required :
• Languages: Expert Python (async, typing, Pydantic, testing); working proficiency in TypeScript and SQL
• LLMs and GenAI: Hands-on with frontier models (Claude, GPT, or equivalent), structured outputs, function and tool calling, context engineering, and prompt design
• Agent frameworks: Production experience with LangGraph (strongly preferred) or comparable frameworks such as LangChain, LlamaIndex, or the OpenAI Agents SDK
• Retrieval: Vector databases and search services (Databricks Vector Search, Azure AI Search, pgvector, or similar), embedding models, hybrid retrieval, and reranking
• Backend: FastAPI, REST and streaming protocols (SSE, WebSockets), async I/O, and OAuth2 or Entra ID authentication
• Frontend: React, TypeScript, state management, and component libraries; able to build streaming chat and dashboard interfaces
• Data platform: Databricks (Model Serving, Unity Catalog, MLflow, Databricks Apps) or an equivalent enterprise data and AI platform
• Cloud and DevOps: Microsoft Azure, Docker, Git, and CI/CD using GitHub Actions or Azure DevOps
• LLMOps: Evaluation frameworks, tracing and observability (MLflow Tracing, LangSmith, or similar), and cost and latency monitoring Preferred
• Model Context Protocol (MCP) and agent-to-agent interoperability patterns
• Databricks Genie, Mosaic AI Agent Framework, or Agent Bricks
• Realtime voice and speech APIs (Azure AI Speech, GPT-Realtime, or similar)
• Multilingual or Arabic NLP
• Integration with enterprise systems such as CRM, ERP, Microsoft Teams, and Power Automate
• Kubernetes, Terraform, or Databricks Asset Bundles
Qualifications :
• 4 to 10 years of software or ML engineering experience, including at least 2 years building LLM or generative AI applications
• A proven track record of shipping at least one GenAI or agentic application to production with real users
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Strong system design skills, with the ability to reason about reliability, security, and cost trade-offs
• Clear written and verbal communication with both technical and business stakeholders
• Relevant certifications (Databricks Generative AI Engineer, Azure AI Engineer) are a plus
For more details, please inbox : moumita.p@dautom.com

Work arrangement
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