Hiring AI & LLM Engineer with Datamatics For Mumbai/Bangalore

Datamatics; Mumbai, Bengaluru; Híbrido; INR 2.000.000 - 4.000.000; Jornada completa

Descripción de la vacante

Datamatics is seeking an AI Engineer to design, implement and iteratively enhance AI agents, chatbots and voice-bot workflows. You will work with LLM patterns, RAG, and tool calling while integrating Gemini/Vertex AI or OpenAI through robust interfaces.

You will build grounding, guardrails and escalation paths, create evaluation datasets, and collaborate with Solution Architecture, Software/Integration and Operations to ensure observability and cost control across knowledge sources and channels.

Formación

• Hands-on experience building software or AI solutions with Python.
• Experience integrating HTTP APIs.
• Familiarity with LLMs, prompt engineering, RAG, embeddings, tool calling.
• Exposure to cloud AI platforms or model APIs; conversational AI/voice bots is useful.
• Understanding testing/evaluation for probabilistic systems, including grounding, safety, latency, reliability and cost considerations.

Responsabilidades

• Design, develop and iterate AI agents, chatbots and voice-bot workflows.
• Implement LLM patterns including prompt design, retrieval-augmented generation (RAG), tool/function calling, conversation state and structured outputs.
• Integrate cloud AI platforms through maintainable interfaces (Gemini/Vertex AI/OpenAI).
• Build grounding, guardrails, refusal behavior, escalation paths and human-in-the-loop controls.
• Create repeatable evaluation datasets and tests; measure answer quality, latency and model cost.
• Collaborate with Solution Architecture, Software/Integration and Operations to connect knowledge sources and systems.
• Instrument solutions for observability and improve prompts, retrieval, or model choices.
• Document decisions and operational guidance for handover and governance review.

Conocimientos

Python

APIs integration

LLMs & prompt engineering

RAG & embeddings

Cloud platforms (Gemini/Vertex AI/Open

Educación

Bachelor's degree in Computer Science, Engineering, Data Science or related discipline

Herramientas

HTTP APIs integration

Descripción del empleo

ROLE SUMMARY

Build and evaluate the intelligence layer of AI solutions for customer-management and Digital Experiences use cases. The Engineer develops agent, chatbot and voice-bot workflows using large language models, retrieval and tool integrations, with a focus on safe, measurable and operationally reliable behavior.

KEY RESPONSIBILITIES

• Design, develop and iterate AI agents, chatbots, voice-bot workflows and agent-assist capabilities based on approved use cases and solution requirements.
• Implement LLM patterns including prompt design, retrieval-augmented generation (RAG), tool/function calling, conversation state and structured outputs.
• Integrate selected model and cloud platforms such as Gemini/Vertex AI, OpenAI or other approved services through maintainable interfaces.
• Build grounding, guardrails, refusal behavior, escalation paths, validation and human-in-the-loop controls appropriate to the use case and risk.
• Create repeatable evaluation datasets and tests; measure answer quality, task completion, groundedness, hallucination/error rates, latency and model cost.
• Collaborate with Solution Architecture, Software/Integration and Operations to connect knowledge sources, APIs, workflows, telephony/contact-center channels and business systems.
• Instrument solutions for observability and feedback; investigate failures and regressions and improve prompts, retrieval, orchestration or model choices.
• Document technical decisions, model/configuration changes, known limitations, test evidence and operational guidance for handover and governance review.

QUALIFICATIONS & EXPERIENCE

• Bachelors degree in Computer Science, Engineering, Data Science or a related discipline, or equivalent practical experience.
• Hands‑on experience building software or AI solutions with Python or a comparable language and integrating HTTP APIs.
• Practical familiarity with LLMs, prompt engineering, RAG, embeddings/vector search, tool calling and structured response formats.
• Experience with one or more approved cloud AI platforms or model APIs; exposure to conversational AI, voice bots or contact‑center solutions is useful.
• Understanding of testing and evaluation for probabilistic systems, including grounding, safety, latency, reliability and cost considerations.

CORE COMPETENCIES

Strong software engineering discipline, experimentation and analytical debugging. Security- and privacy-aware handling of prompts, data, tools and model outputs. Ability to explain model behavior, limitations and evaluation evidence to technical and operational partners.

KEY STAKEHOLDERS

AI & Transformation Lead; Solution Architect/Business Analyst; Software/Integration Developer; Operations and SMEs; Technology, Security and Data teams; platform vendors.

KEY SUCCESS MEASURES

• Quality and reliability against approved task, safety and grounding evaluation criteria.
• Production performance for task completion, escalation, latency, availability and model cost.
• Timely delivery of tested, maintainable components with documented limitations and controls.
• Reduction in material errors and successful resolution of issues identified from monitoring and user feedback.