Job Summary:
We are seeking an AI-Native Software Engineer who views AI not just as an autocomplete tool, but as a core collaborative partner in software delivery. In this role, you will spend less time manually writing boilerplate and more time architecting systems, designing precise technical specifications, and orchestrating multi-agent workflows.
Core Responsibilities
- System Architecture & Design: Define high-level system structures, API contracts, and data models before instructing AI tools to implement them. Own the design, not just the execution.
- Context Engineering & Spec Writing: Author rigorous, unambiguous technical specifications and context rules to guide AI agents toward deterministic, reviewable outputs.
- RAG Pipeline Design: Architect and own end-to-end Retrieval-Augmented Generation pipelines, document ingestion, chunking strategy, embedding selection, vector store configuration, hybrid retrieval, and relevance evaluation.
- Agentic Workflow Management: Build and operate agent harnesses using orchestration frameworks (e.g. LangGraph, LangChain, AutoGen) including tool definitions, routing logic, guardrails, fallback paths, and evaluation hooks.
- Human-in-the-Loop Validation: Design and enforce HITL gates for agentic write operations. Know when to automate and when to require human sign-off, especially for irreversible or high-stakes actions.
- Review, test, and audit AI-generated code for security vulnerabilities, performance characteristics, edge cases, and architectural alignment before it reaches production.
Required Technical Skills
- Engineering Fundamentals: Strong mastery of computer science fundamentals — data structures, algorithms, distributed systems, and system design. You must be able to catch and correct AI errors because you understand the underlying systems.
- Code Review & Auditing: Exceptional ability to read, evaluate, and critique AI-generated code across multiple languages rapidly.
- Agentic System Design: Hands-on production experience building agent harnesses, multi-agent orchestration pipelines, and supervisor/routing patterns using frameworks such as LangGraph, LangChain, or equivalent.
- RAG & Retrieval Engineering: Practical experience designing RAG pipelines including vector store selection, embedding strategies, hybrid search, Reciprocal Rank Fusion, and retrieval quality evaluation.
- AI Tooling Proficiency: Advanced hands-on experience with AI-native IDEs (e.g. Cursor, Windsurf, GitHub Copilot) and command-line agentic tools (e.g. Claude Code, Aider, Codex CLI).
- Context & Prompt Engineering: Proven ability to manage AI context windows, system instructions, tool schemas, and prompt structure to produce consistent, auditable outputs.
- Cloud & API Integration: Solid experience with cloud-native deployment (Azure, AWS, or GCP), RESTful API design, async patterns, and enterprise identity/auth integration.
- Testing & CI/CD: Strong experience writing automated test suites to validate AI-generated logic inside modern CI/CD pipelines, including adversarial and edge-case coverage.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Software Engineering, or equivalent deep production experience.
- Experience integrating with enterprise HR, workforce, or ERP platforms (e.g. SAP SuccessFactors, Workday, Concur, or Oracle HCM) — particularly in an agentic or API integration context.
- Hands-on ML experience beyond API consumption: model fine-tuning, training pipelines, evaluation frameworks, or MLOps deployment.
- Familiarity with enterprise identity providers (e.g. OKTA, Azure AD) and secure token handling in agentic contexts.
- A portfolio or GitHub repository demonstrating projects built primarily via agentic or spec-driven development methodologies.
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
