Large Language Model Architect

Accenture; Coimbatore District; On-site; INR 400,000 - 700,000; Full time

Job summary

Accenture in India seeks a Large Language Model Architect to design, build and operate enterprise-grade LLM components. You will own platform-specific engineering on Databricks, translate architecture into production-ready modules for LLM-driven applications and orchestrate RAG pipelines across client engagements.

Bring hands-on coding in Python, experience with AI/ML data products and strong understanding of API-driven, secure systems.

Qualifications

• Bachelor's degree in CS/CE/DS/AI/ML/IT or related engineering.
• Hands-on Python coding with APIs, distributed systems, CI/CD, testing and observability.
• Experience delivering AI/ML or data products in at least one domain such as finance, healthcare, manufacturing, retail, telecom or life sciences.

Responsibilities

• Design and build LLM components: prompts, tools, agents, orchestration flows, memory and retrieval pipelines.
• Implement data-grounded agentic apps on lakehouse; use Delta tables, vector search, and governance features.
• Utilize MLflow for tracing, evaluation and model lifecycle deployment of agents or models.
• Ingest, parse, chunk, enrich data; enable embeddings, vector search and retrieval workflows.
• Build safety controls: PII detection/redaction, prompt-injection defenses, content filters and guardrails.
• Collaborate with architects, data engineers, product owners and security to deliver tested software.

Skills

Generative AI

Python

APIs

CI/CD

Observability

Secure SDLC

Distributed systems

Databricks Mosaic AI

Model Serving

Agent Framework

MLflow

Vector Search

Unity Catalog

Delta Lake

Lakehouse Monitoring

Feature Store

Databricks Workflows

Education

15 years full time education

Tools

Databricks

Databricks Mosaic AI

Model Serving

Agent Framework

MLflow

Vector Search

Unity Catalog

Delta Lake

Lakehouse Monitoring

Feature Store

Databricks Workflows

Job description

Project Role : Large Language Model Architect

Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.

Must have skills : Generative AI

Good to have skills : Databricks Unified Data Analytics Platform

Minimum 5 year(s) of experience is required

Educational Qualification : 15 years full time education

Role Summary / Description

AI Powered Tech Talent

Engineer role in AI LLM Technology Architecture. Hands-on engineering role focused on designing, building, integrating, testing and operationalizing enterprise-grade LLM, GenAI and agentic AI components across active client engagements.

Own platform-specific engineering on Databricks, translating high-level architecture into working, production-quality components for LLM-driven applications, RAG pipelines, multi-agent workflows and AI platform integrations.

Bring practical industry experience in financial services, healthcare, manufacturing, retail, telecom or life sciences to identify domain data, process constraints, controls and adoption risks while designing GenAI solutions that are safe, scalable and relevant.

Operate as a hands-on technical lead or engineering lead, contributing code, design decisions, reusable patterns and engineering documentation.

Key Responsibilities

• Design and build LLM application components including prompts, tools, agents, orchestration flows, memory/context handling, retrieval pipelines and evaluation harnesses.
• Build data-grounded agentic applications on the lakehouse implement RAG with Delta tables, Vector Search and governed features use MLflow for tracing, evaluation and model lifecycle deploy agents or models with Model Serving and enforce governance through Unity Catalog.
• Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search and retrieval workflows for structured and unstructured enterprise content.
• Engineer safety and control components including PII detection/redaction, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage and audit logging.
• Collaborate with architects, data engineers, product owners and security stakeholders to convert solution designs into tested, observable and maintainable software components.
• Maintain technical artifacts such as component designs, integration specifications, deployment runbooks, evaluation results and reusable engineering patterns.

Required Qualifications

• Bachelor s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology or a related engineering discipline.
• Hands‑on coding experience in Python and strong understanding of APIs, distributed systems, CI/CD, testing, observability and secure SDLC practices.
• Experience delivering AI/ML or data products in at least one industry domain such as financial services, healthcare, manufacturing, retail, telecom or life sciences.

Required Skills/ Experience

• Hands‑on experience with Databricks Mosaic AI, Model Serving, Agent Framework, MLflow tracing/evaluation, Vector Search, Unity Catalog, Delta Lake, Lakehouse Monitoring, Feature Store, Databricks Workflows, Jobs, notebooks and Model Training.
• Strong understanding of LLM application architecture patterns including RAG, function/tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases and evaluation metrics.
• Ability to implement traditional ML and GenAI components across ingestion, feature/data preparation, model integration, deployment, monitoring and continuous improvement.
• Practical knowledge of security, privacy, governance, performance, scalability, reliability and cost controls for production AI systems.
• Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure-as-code and agile delivery in client-facing environments.

Good to Have Skills

• Databricks Machine Learning, Data Engineer or Generative AI certification experience with Spark/PySpark, Delta Live Tables, Unity Catalog governance, LangGraph/LangChain, model fine-tuning and lakehouse cost/performance optimization.
• Exposure to open-source frameworks such as LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker and Kubernetes.
• Experience with Responsible AI, model risk management, synthetic data generation, human-in-the-loop review, A/B testing and GenAI cost optimization.
• 15 years full time education

Equal Employment Opportunity Statement

All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.

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