Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Machine Learning
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary
Lead the design and delivery of AI solutions across Agentic AI, Generative AI (LLMs) and classical ML/CV. Own the technical direction for suggestion & rules frameworks, search/retrieval, document and web data extraction, and image/OCR pipelines for the Value Stream. Provide architectural leadership, mentor engineers, and ensure production-grade quality, safety, and reliability. Should be familiar with evaluation strategies, responsible AI, explainability.
Responsibilities
Define end-to-end architecture for LLM/agent systems (tool use, orchestration, guardrails) and classical ML components.
Design suggestion engines and policy/rule layers that combine deterministic constraints with generative outputs.
Architect search & retrieval (BM25 + embeddings) and RAG pipelines drive relevance tuning and evaluation.
Oversee robust scraping & extraction (Playwright/Selenium/Trafilatura) and structured normalization (JSON/Parquet, schema validation).
Direct image processing and OCR workflows (OpenCV, pytesseract/ocrmypdf) for document understanding.
Establish evaluation strategy: offline/online experiments, quality/latency/cost KPIs integrate DeepEval for unit-style LLM tests.
Guide data governance, privacy/PII handling, and secure model/agent operations with MLOps partners.
Mentor the team, run design reviews, and produce clear design docs, RFCs, and POVs for stakeholders.
Concepts & Technical Awareness (Expected)
Model generalization vs. overfitting/underfitting bias/variance trade-offs regularization and early stopping.
Deep learning fundamentals: CNNs, RNNs/LSTMs/GRUs, and modern transformers encoder/decoder architectures and attention.
LLM inner-workings at a practical level: tokenization, context windows, inference strategies (batching, caching, quantization), fine-tuning/PEFT, and RAG.
Inference and serving techniques for throughput/cost (vectorization, mixed precision, compile/acceleration paths where applicable).
Professional & Technical Skills:
PyTorch Hugging Face ecosystem (transformers, datasets, sentence-transformers/SBERT) BERT/Llama families as applicable.
LangChain for orchestration familiarity with LangGraph/LangMem for agentic workflows (subject to approval).
spaCy, scikit-learn LightGBM/Flair where relevant Optuna for HPO SHAP for model explainability.
Search: Elastic/OpenSearch vector stores (FAISS/Pinecone/pgvector) docarray for embedding flows.
Document & web data: Playwright/Selenium, Trafilatura, pypdf, pdfplumber, pdfkit tokenization tools like tiktoken.
Stakeholder demos: Streamlit (local-only).
Qualifications
Proven record architecting and shipping production ML/LLM systems.
Strong written and verbal communication experience leading Agile delivery and cross-functional collaboration.
You will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions
Proven experience in cloud, DevOps, or AI modernization initiatives.
Strong understanding of LLMs, automation, and engineering toolchains.
Ability to translate AI innovation into business and productivity impact.
Additional Information:
- The candidate should have minimum 7.5 years of experience in Machine Learning.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.15 years full time education
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Machine Learning
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary
Lead the design and delivery of AI solutions across Agentic AI, Generative AI (LLMs) and classical ML/CV. Own the technical direction for suggestion & rules frameworks, search/retrieval, document and web data extraction, and image/OCR pipelines for the Value Stream. Provide architectural leadership, mentor engineers, and ensure production-grade quality, safety, and reliability. Should be familiar with evaluation strategies, responsible AI, explainability.
Responsibilities
Define end-to-end architecture for LLM/agent systems (tool use, orchestration, guardrails) and classical ML components.
Design suggestion engines and policy/rule layers that combine deterministic constraints with generative outputs.
Architect search & retrieval (BM25 + embeddings) and RAG pipelines drive relevance tuning and evaluation.
Oversee robust scraping & extraction (Playwright/Selenium/Trafilatura) and structured normalization (JSON/Parquet, schema validation).
Direct image processing and OCR workflows (OpenCV, pytesseract/ocrmypdf) for document understanding.
Establish evaluation strategy: offline/online experiments, quality/latency/cost KPIs integrate DeepEval for unit-style LLM tests.
Guide data governance, privacy/PII handling, and secure model/agent operations with MLOps partners.
Mentor the team, run design reviews, and produce clear design docs, RFCs, and POVs for stakeholders.
Concepts & Technical Awareness (Expected)
Model generalization vs. overfitting/underfitting bias/variance trade-offs regularization and early stopping.
Deep learning fundamentals: CNNs, RNNs/LSTMs/GRUs, and modern transformers encoder/decoder architectures and attention.
LLM inner-workings at a practical level: tokenization, context windows, inference strategies (batching, caching, quantization), fine-tuning/PEFT, and RAG.
Inference and serving techniques for throughput/cost (vectorization, mixed precision, compile/acceleration paths where applicable).
Professional & Technical Skills:
PyTorch Hugging Face ecosystem (transformers, datasets, sentence-transformers/SBERT) BERT/Llama families as applicable.
LangChain for orchestration familiarity with LangGraph/LangMem for agentic workflows (subject to approval).
spaCy, scikit-learn LightGBM/Flair where relevant Optuna for HPO SHAP for model explainability.
Search: Elastic/OpenSearch vector stores (FAISS/Pinecone/pgvector) docarray for embedding flows.
Document & web data: Playwright/Selenium, Trafilatura, pypdf, pdfplumber, pdfkit tokenization tools like tiktoken.
Stakeholder demos: Streamlit (local-only).
Qualifications
Proven record architecting and shipping production ML/LLM systems.
Strong written and verbal communication experience leading Agile delivery and cross-functional collaboration.
You will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions
Proven experience in cloud, DevOps, or AI modernization initiatives.
Strong understanding of LLMs, automation, and engineering toolchains.
Ability to translate AI innovation into business and productivity impact.
Additional Information:
- The candidate should have minimum 7.5 years of experience in Machine Learning.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.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
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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.
