The Role
Design, build, and operationalize production-grade LLM, GenAI, and agentic AI solutions on Databricks. Develop RAG pipelines, data ingestion workflows, vector search, model integrations, evaluation systems, and governance controls. Implement security, privacy, observability, and scalability practices while collaborating with architects, data engineers, product owners, and security stakeholders. Lead hands-on engineering through coding, testing, deployment, documentation, and continuous improvement.
Summary Generated by Built In
Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : Large Language Models (LLMs)
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
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : Large Language Models (LLMs)
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.
Skills Required
- Minimum 7.5 years of professional experience
- 15 years of full-time education
- 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
- 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 specified industry domain
- 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, 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, 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
- Databricks Machine Learning, Data Engineer, or Generative AI certification experience
- Experience with Spark/PySpark, Delta Live Tables, Unity Catalog governance, LangGraph/LangChain, model fine-tuning, and lakehouse cost/performance optimization
- Exposure to 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
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Parental & Family Support — Parental leave and family-planning perks are described as comprehensive, including paid leave for birth and non-birth parents, fertility and surrogacy assistance, adoption support, and subsidized backup care. These offerings make the package notably supportive for those prioritizing family resources.
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Retirement Support — Retirement programs feature dollar-for-dollar 401(k) matching for eligible employees as part of a strong savings emphasis. This structure supports steady long-term wealth building beyond base pay.
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Healthcare Strength — Health coverage includes multiple plan choices such as PPO, EPO, and HDHP options along with dental and vision. Mental-health and assistance resources add breadth to the overall care ecosystem.
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The Company
What We Do
Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 500,000+ people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com.
