Senior Forward-Deployed AI Engineer / AI Architect

Total Experience: 15–20 Years (including 2+ years of hands-on Generative AI / Agentic Systems experience)

About the Role

Cognizant is seeking an experienced Senior Forward-Deployed AI Engineer to join our Strategic AI practice. In this leadership role, you will bridge the gap between complex Generative AI engineering and high-impact business solutions for domain-specific accounting, audit, and tax workflows.

You will lead the design and implementation of enterprise-grade AI applications using Large Language Models (LLMs), Agentic frameworks, document intelligence, and advanced Retrieval-Augmented Generation (RAG) pipelines at scale.

Key Responsibilities & Deliverables

• Scalable AI Architecture: Design and deploy enterprise LLM applications that deliver high-precision results while managing model cost optimization, token allocation budgets, and AI governance standards.

• Accounting & Tax Domain Solutions: Build automated workflows for financial statement reviews, document classification, evidence extraction, and complex document intelligence across unstructured financial sources (PDFs, scans, and forms).

• Advanced RAG & Document Intelligence: Construct RAG ingestion pipelines and structured extraction workflows to parse complex data into high-accuracy knowledge representations.

• Evaluations & Model Optimization: Implement evaluation techniques including LLM-as-a-Judge, Direct Preference Optimization (DPO), and human-in-the-loop validation to benchmark and improve model accuracy.

• Agentic Frameworks & Auto-Coding: Leverage agentic frameworks and modern developer tools (Claude Code, GitHub Copilot) to accelerate delivery from spec to deployment.

• Client & Stakeholder Communication: Articulate technical trade-offs, AI capabilities, and architectural decisions to executives, client partners, and engineering teams.

Technology Stack

• Languages & Frameworks: Python, Django, React, TypeScript, Jinja, Agentic Frameworks (LangGraph, Claude Agent SDK, OpenAI Agents SDK, Google ADK)

• Cloud & Infrastructure: Azure Cloud Services (Containers, APIs, CI/CD, Monitoring)

• Data & Vector Databases: PostgreSQL, pgvector , OpenSearch, Azure AI Search, Pinecone, or Weaviate

• AI & Developer Tooling: Claude Code, GitHub Copilot, Modern LLM APIs, Prompt Engineering, RAG Frameworks

Required Qualifications

• Experience: 15 to 20 years of overall software engineering and architecture experience, with at least 2 years of focused, hands-on experience building production Generative AI/LLM solutions.

• LLM & RAG Expertise: Extensive hands-on experience in prompt engineering, RAG architectures, evaluation methodologies, and managing LLM failure modes (hallucinations, grounding, context windows).

• Full-Stack Proficiency: Proven track record across UI, API, Database, and Backend execution (Python, Django, React, TypeScript).

• Vector Search & Storage: Hands-on experience with vector databases and embedding-based retrieval systems (e.g., pgvector , Azure AI Search, Pinecone).

• Cloud Platforms: Experience building, containerizing, and deploying cloud-native applications on Microsoft Azure.

• AI Coding Tools: Experience utilizing AI-assisted coding tools like Claude Code and GitHub Copilot to build according to precise specifications.

• Communication: Exceptional oral and written communication skills with the ability to lead enterprise client engagements.

Nice-to-Have Skills & Qualifications

• Experience with Graph RAG or specialized Document Intelligence services.

• Direct domain exposure to CPA, accounting, audit, or tax workflows and software applications.

• Familiarity with accounting principles and regulatory standards (e.g., GAAP, GAAS, PCAOB, IFRS, IRC).

• Willingness to travel occasionally for key client workshops or team meetings.