Role Description
Frontier Engineer
Sets enterprise AI architecture and responsible-AI standards; designs AI delivery at scale across pods and accounts.
ABOUT THE ROLE
The senior technical leader who designs the enterprise-scale AI systems behind Cognizant's most complex client transformations. Defines human-agent capability matrices, authors guardrail specifications, leads client architecture workshops, and owns the intellectual design of AI delivery at scale, cross-domain, cross-platform and cross-sector. From responsible-AI governance to regulated decisioning systems, the Distinguished Frontier Engineer sets the standard rather than meeting it, and technically leads cohorts of Frontier Engineers and Masters.
WHAT YOU WILL DO
- Design AI-native enterprise architectures and define human-agent capability matrices for delivery programmes.
- Author guardrail specifications and boundary documentation for agentic systems at enterprise scale.
- Lead client architecture review workshops and produce context-pipeline blueprints.
- Govern ADLC adoption across the portfolio; define standards for AI-generated code quality.
- Architect responsible-AI frameworks: bias detection, explainability and audit-trail design.
- Design regulated AI decisioning systems with compliance controls for relevant domains.
WHAT YOU BRING
Core skills: AI-native enterprise architecture, Guardrail specification & responsible-AI framework design, Context-pipeline architecture at scale, ADLC delivery governance, Cross-platform AI integration strategy, AIOps orchestration architecture, Regulated AI decisioning design, Frontier-model evaluation & red-teaming, Human-agent capability modelling.
Competencies: Enterprise AI Architecture, Responsible-AI & Guardrail Design, ADLC Governance & Standards, Technical Leadership & Advisory, AI Quality & Evaluation Design, Domain Fluency & Contextual Judgment, Business-Outcome Orientation.
ENTRY AND GROWTH
Experience: 12-20 yrs with enterprise AI architecture leadership.
Entry: Demonstrate enterprise-scale AI architecture and responsible-AI leadership; pass the Frontier CoE assessment at Architect level.
WHAT SUCCESS LOOKS LIKE
Builds, ships and permanently owns AI-native systems end to end in a small Frontier pod, and is measured on the customer outcome the pod commits to, not on technical throughput alone.
Salary and Other Compensation:
The annual salary for this position is between $180K ++ 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.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- 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
Disclaimer: The salary, other compensation, and benefits 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.
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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