Associate Partner Consulting, AI

About the Role

The Forward Deployed Context Engineering Lead (Director) is responsible for designing, deploying, and governing end-to-end context and retrieval architectures that power generative AI and agentic AI solutions for strategic financial services clients. Embedded at client sites using a embedded forward deployment model, this leader translates business imperatives into production-grade AI deployments, context pipelines, tool orchestration frameworks, and evaluation systems that ensure AI workflows are compliant, reliable, and measurable against regulatory and business standards.

Key Responsibilities

• Partner with CFO, CIO, COO, Chief Risk Officer, and Chief Compliance Officer to define multi-year AI transformation roadmaps, with emphasis on use case prioritization, governance alignment, and risk-adjusted ROI.
• Work "forward deployed" at client sites, embedding within business units and technology teams to own end-to-end solution delivery from discovery through production and value realization.
• Lead discovery workshops to uncover high-value AI opportunities, frame problem statements, and shape outcome-driven implementations in core business processes (credit decisioning, market risk, AML/CFT, wealth advisory).

End-to-End Context Architecture

• Own the complete context fabric that feeds LLMs and agents: data products, RAG pipelines, vector databases, knowledge graphs, semantic layers, tool schemas, memory stores, and orchestration patterns.
• Design and oversee implementation of enterprise-scale retrieval systems that integrate multiple data sources (core banking, risk repositories, regulatory data, market data, customer data warehouses) with sub-second latency and high recall.
• Architect tool landscapes for agents, defining function schemas, validation rules, pre/post-execution guardrails, and escalation patterns so agents safely interact with core systems (core banking APIs, trading platforms, CRM, regulatory reporting engines).

AI & Data Governance & BCBS 239 Alignment

• Embed data lineage, quality controls, and metadata management into context pipelines to satisfy BCBS 239 principles (completeness, accuracy, timeliness, clarity, granularity) and emerging AI data governance expectations.
• Work with Chief Data Officer and data governance teams to ensure context data products meet regulatory lineage requirements, audit trails, and change management protocols.
• Design data product contracts that codify context completeness, freshness, and accuracy SLAs and make them machine-readable for automated quality gates.

AI Evaluation & Safety Strategy

• Define and operationalize comprehensive evaluation strategy covering accuracy, consistency, hallucination detection, bias, fairness, latency, cost, and regulatory compliance by use case.
• Establish baseline and continuous metrics for both offline benchmarking (held-out test sets, red teaming) and online monitoring (production feedback, human review, alert escalations).
• Partner with Evaluation Engineering and Risk teams to implement automated quality gates in CI/CD pipelines, blocking unsafe or regressing models/prompts/context changes from deployment.

Responsible AI & Governance Integration

• Translate NIST AI RMF, ISO 42001, EU AI Act, and internal governance policies into architecture requirements: explainability, auditability, bias monitoring, human oversight, incident response.
• Collaborate with Chief Risk Officer, compliance, legal, and audit to define AI governance controls: model risk management, data governance, algorithm risk registers, impact assessments, and escalation workflows.

Cloud & Platform Strategy

• Own technical platform strategy for AI solutions, including cloud selection (AWS, Azure, GCP), data platform selection (Snowflake, Databricks, Palantir Foundry, Microsoft Fabric), and integration architecture.
• Architect secure, scalable, multi-tenant AI infrastructure that meets financial services standards for security, auditability, disaster recovery, and regulatory reporting.

Business Development & Executive Engagement

• Support go-to-market strategy for AI transformation engagements: solutioning, proposals, statement of work (SOW) development, and executive presentations to C-suite.
• Build thought leadership content (whitepapers, case studies, reference architectures) on context engineering, AI governance, and financial services AI transformation.
• Mentor and grow a practice or delivery team of context engineers, evaluation engineers, platform engineers, and solution architects to scale repeatable AI capability.

Work Arrangements

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in Dallas, Minneapolis, or Chicago. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

Requirements

• 15+ years of experience across software engineering, data engineering, data science, or AI/analytics, with at least 5-7 years leading AI/ML transformation initiatives.
• Proven track record leading large-scale AI or digital transformation programs at consulting firms (Deloitte, PwC, Accenture, Cognizant) or equivalent director/senior manager roles in financial services technology.
• Demonstrated expertise working in a forward-deployed or embedded model, owning end-to-end solution delivery from architecture through production launch and ongoing optimization.
• Hands-on technical expertise in modern AI stacks: LLMs, RAG, vector databases, cloud platforms, and ML engineering practices.
• Prior experience in financial services (investment banking, capital markets, wealth management, payments, insurance) or other regulated domains (healthcare, government).

Preferred Qualifications

• Deep, hands-on understanding of LLM architecture, capabilities, limitations, and fine-tuning approaches; experience with GPT-4, Claude, LLaMA, and domain-specialized models.
• Advanced expertise in multi-agent orchestration patterns: hierarchical agents, collaborative agents, tool-using agents, memory strategies, and long-horizon planning for financial workflows.
• Proficiency with prompt engineering, in-context learning, chain-of-thought, and few-shot prompting for complex financial reasoning tasks (credit analysis, risk assessment, advisor-style interactions).

About Cognizant

Cognizant is one of the worlds leading professional services companies, transforming clients business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World's Best Employers 2025) is consistently listed among the most admired companies in the world.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Cognizant Community

We are a high-caliber team who appreciate and support one another. Our people uphold an energetic, collaborative and inclusive workplace where everyone can thrive.

Work Authorization

Cognizant will only consider applicants for this position who are legally authorized to work in the United States without company sponsorship (H-1B, L-1B, L-1A, etc.).

Salary and Other Compensation

The annual salary for this position is between $137,250 - $250,500 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.

Disclaimer

Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.