Role at a glance
- Job function
-
AI & Data Large Language Model (LLM) Engineering
- Salary
- Not Disclosed
- Location
- Bengaluru
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- Minimum 7.5 year(s) of experience is required
- Education
- 15 years full time education
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Role Summary
This hands-on engineering role focuses on designing, building, integrating, testing and operationalizing enterprise-grade LLM, GenAI and agentic AI components across client engagements. The role owns platform-specific engineering on Databricks for LLM-driven applications, RAG pipelines, multi-agent workflows and AI platform integrations, with attention to domain data, controls and production governance.
What You'll Do
- Design and build LLM application components including prompts, tools, agents, orchestration flows, memory/context handling, retrieval...
- Build data-grounded agentic applications on the lakehouse using RAG, Delta tables, Vector Search, MLflow, Model Serving and Unity Catalog.
- Implement data ingestion, parsing, chunking, enrichment, embeddings, vector search and retrieval workflows for structured and...
- Engineer safety and control components including PII detection/redaction, prompt-injection defenses, content filters, guardrails,...
- Collaborate with architects, data engineers, product owners and security stakeholders to convert solution designs into tested,...
- Maintain technical artifacts such as component designs, integration specifications, deployment runbooks, evaluation results and reusable...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Generative AI; Python; APIs; distributed systems; CI/CD; testing; observability; secure SDLC; Databricks Mosaic AI, Model Serving, Agent Framework, MLflow, Vector Search, Unity Catalog and Delta Lake; LLM application architecture including RAG, tool calling, agent orchestration, prompt engineering, embeddings and vector databases; experience delivering AI/ML or data products in an industry domain.
Required
- Hands-on coding experience in Python
- 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,...
- Hands-on experience with Databricks Mosaic AI, Model Serving, Agent Framework, MLflow tracing/evaluation, Vector Search, Unity Catalog,...
- Strong understanding of LLM application architecture patterns including RAG, function/tool calling, agent orchestration, model...
- Ability to implement traditional ML and GenAI components across ingestion, feature/data preparation, model integration, deployment,...
- 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...
Preferred
- Databricks Unified Data Analytics Platform
- 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...
- 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...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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 7.5 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
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
About the company
Accenture
Large Enterprise
Accenture is a global professional services company that specializes in providing consulting, technology, and outsourcing services. With a diverse range of industries served, including financial services, healthcare, and telecommunications, Accenture leverages advanced technologies and data analytics to help organizations improve their performance and drive innovation. Committed to sustainable progress, the company emphasizes its dedication to inclusivity, digital transformation, and building a more sustainable future for its clients and communities. With a presence in over 120 countries, Accenture is known for its expertise in integrating cutting-edge solutions that address complex business challenges.