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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Forward Engineer - **Company:** CGI Technologies and Solutions, Inc. - **Location:** Fairfax, VA, United States - **Experience:** Expert - **Salary:** $89,600.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Engineering, Code Coverage, Code Review, Cyber Security, Information Technology Consulting, Cursor, Github, Automation of Marketing, Systems Development Life Cycle, Rapid Prototyping Process, OpenAI, Microsoft Copilot, Software Engineering, Working Model 2D, Openapi, Enterprise Data Management, Retrieval-Augmented Generation, Large Language Models, Claude Code, Multi-Agent Systems, Prompt Engineering, IT Architecture, Generative AI, AI Coding Agents, Agentic-AI, AI Platforms, Gherkin, Machine Learning Operations, Devsecops, Microservices - **Published:** November 5, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3496657171&tx=FP5148FFL&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role 10+ years in enterprise technology, software engineering, or IT consulting, with 5+ years in a senior client facing role. . Proven track record leading AI Native SDLC adoption in enterprise delivery environments. . Hands on experience designing or using AI agents for coding, testing, code review, and remediation. . Fluency with AI coding tools (i.e. Copilot, Cursor, Windsurf, Amazon Q, Claude Code, or similar). . Ability to set governance, quality gates, and adoption metrics for AI assisted engineering teams. . Strong hands on expertise with LLMs, RAG, and enterprise AI platforms (Bedrock, Vertex AI, Azure OpenAI, LangChain). . Solid grounding in cloud native architecture, APIs, microservices, and cybersecurity. . Working knowledge of vector databases, prompt engineering, and agent orchestration. . Ability to quickly learn a client's business and spot where AI drives real transformation. . Excellent communicator, comfortable translating technical concepts for executives and engineers alike. . Experience leading workshops, demos, and executive presentations with a consulting mindset. . Bachelor's degree in a related technical field; advanced degree preferred. Preferred Qualifications . Experience scaling AI Native SDLC across multiple teams or delivery portfolios. . Background in public sector, healthcare, financial services, or other regulated industries. . Experience supporting proposals, solutioning, or strategic pursuits. . Familiarity with responsible AI, model risk, and enterprise automation platforms. . Active or prior U.S. government security clearance. Skills AI Native SDLC | Agentic Software Engineering | AI Assisted Development | DevSecOps | Platform Engineering | Generative AI | AI Architecture | Retrieval Augmented Generation | Agentic AI | Intelligent Automation | Cloud Architecture | Enterprise Architecture | Responsible AI | Technical Leadership | Client Advisory | Business Transformation | Executive Communication | Consulting ## Description CGI is looking for senior, client facing engineer who can help organizations put AI to work across the entire software delivery lifecycle. This person will sit at the intersection of AI architecture, agentic software engineering, and transformation advisory, working directly with client executives and delivery teams to redesign how software gets planned, built, tested, secured, modernized, and operated. The ideal candidate has real hands on experience embedding AI coding assistants, software engineering agents, and multi agent workflows into day to day delivery. From requirements and architecture through coding, testing, security, and release and knows how to turn that experience into a governed, repeatable capability rather than a one off pilot. Success means shaping an AI Native SDLC vision with senior leaders, standing up prototypes that prove the value, and building an adoption roadmap with measurable gains in speed, quality, security, and developer experience. CGI will consider candidates proximate to any U.S. office. CGI utilizes a hybrid working model and partners should be prepared to work on site at a CGI or client office, as needed. Your Future Duties and Responsibilities Client Advisory and AI Transformation . Partner with client business and technology leaders to pinpoint where AI can drive real operational, financial, or delivery impact, and translate that into use cases, pilots, and production roadmaps. . Act as a senior technical advisor embedded with client and CGI teams, helping them move past experimentation into secure, governed, measurable AI adoption. . Lead discovery sessions, design workshops, architecture reviews, and executive briefings, and guide clients in rethinking operating models and workforce enablement for AI native ways of working. AI Native SDLC and Agentic Delivery . Lead enterprise adoption of AI Native SDLC, redesigning how teams handle discovery, coding, testing, security, and release with AI agents built in. . Set the governance layer that makes this safe to scale such as quality gates, human in the loop review, and adoption metrics like cycle time and test coverage. . Run prototypes that prove the value for agent assisted delivery, automated testing, legacy modernization and mentor teams on scaling them. . Experience with spec driven development workflows and tooling (e.g., GitHub Spec Kit, Kiro, BMad, OpenAPI/Gherkin) to translate requirements into validated, testable implementations. AI Architecture, Business Value, and Thought Leadership . Architect AI solutions that integrate into enterprise data, cloud, and DevSecOps environments, and lead rapid prototyping through MVP delivery. . Own technical decisions on model orchestration, agent orchestration, and AI observability, and connect them to measurable business outcomes. . Represent CGI in client and executive conversations, mentor architects and engineers, and build CGI's reusable AI delivery assets.