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# Sr. AI. Forward Deployment Engineer

- **Company:** CGI Technologies and Solutions, Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $70,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Microsoft Azure, Cloud Engineering, Code Generation, Code Review, Cyber Security, Information Systems, Information Technology Consulting, Cursor (Graphical User Interface Elements), Programming Tools, Identity and Access Management, Python (Programming Language), Machine Learning, MongoDB, Systems Development Life Cycle, Release Management, Software Engineering, Microsoft Power Automate, GitHub Copilot, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Gitlab, AI Platforms, Information Technology, Graphql, Data Management, Machine Learning Operations, Virtual Agents, Code Restructuring, Network Server, Devsecops, Human in the Loop, Jenkins, Vulnerability Analysis, Microservices
- **Published:** August 27, 2026
- **Apply:** https://www.dallasjobsite.com/job.asp?id=3367081210&tx=VT656THZ&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

At least 10 15 years of experience in Technology Consulting, Digital Transformation, and AI led initiatives

. Strong experience working with US Banking / Financial Services clients

. Required: demonstrated expertise leading or enabling AI Native SDLC adoption in enterprise delivery environments, including how AI changes requirements, architecture, design, coding, testing, security, documentation, DevSecOps, release management, modernization, and operations.

. Required: hands on experience with agentic SDLC practices, including use or design of AI agents for backlog refinement, codebase analysis, software design, code generation, refactoring, code review, test generation, vulnerability analysis, remediation, documentation, and developer support.

. Required: practical experience with AI assisted development tools, agentic IDEs, and software engineering platforms such as GitHub Copilot, GitLab Duo, Cursor, Windsurf, Codeium, Amazon Q Developer, Google Gemini Code Assist, Azure AI Foundry, OpenAI APIs, Claude Code, or similar technologies.

. Required: ability to define AI Native SDLC governance, quality gates, adoption metrics, human in the loop controls, secure coding practices, IP protections, prompt and context management, and responsible use policies for engineering teams.

. Strong hands on expertise with generative AI, LLMs, RAG architectures, AI agents, intelligent automation, and enterprise AI integration.

. Experience designing, prototyping, or delivering AI solutions using modern AI platforms and ecosystems such as Azure OpenAI, OpenAI, Anthropic Claude, AWS Bedrock, Google Vertex AI, Microsoft Copilot Studio, LangChain, LlamaIndex, Semantic Kernel, or similar technologies.

. Strong understanding of enterprise architecture, cloud native design, APIs, microservices, software engineering platforms, data platforms, identity and access management, cybersecurity, and integration patterns.

. Experience with AI solution components such as vector databases, embeddings, model orchestration, prompt engineering, evaluation pipelines, guardrails, AI observability, agent orchestration, context engineering, and LLMOps/MLOps.

. Ability to rapidly understand a client's business, mission, engineering environment, delivery constraints, and modernization priorities, then identify where AI can produce measurable transformation.

. Proven ability to communicate complex AI, software engineering, and technical concepts to executives, business stakeholders, architects, engineers, and non technical audiences.

. Experience leading discovery sessions, AI Native SDLC assessments, architecture workshops, technical demos, prototypes, and executive presentations.

. Ability to operate across strategy, architecture, engineering, delivery, adoption, organizational change, and measurable value realization.

. Strong consulting mindset, including curiosity, ownership, ambiguity tolerance, executive presence, and a bias for practical outcomes.

. Bachelor's degree in computer science, engineering, data science, information systems, or a related field. Advanced degree preferred.

Communication & Consulting Skills

. Excellent storytelling and executive communication skills · Ability to simplify complex AI concepts for non technical senior audiences

. Strong consulting mindset with client first problem solving, * AutoGen

 * Azure
 * Communication
 * Generative AI
 * GraphQL
 * Jenkins
 * LangGraph
 * Large Language Model (LLM)
 * Machine Learning
 * Model Context Protocol Client
 * Model Context Protocol Servers
 * Model Prototyping
 * MongoDB
 * Python

## Description

This role will require someone at our client site 5 days a week in Pittsburgh, PA, Cleveland, OH, or Dallas, TX.

For this role on this particular client engagement, employer sponsorship of immigration related visa and/or green card status as part of the PERM process will not be available.

CGI is seeking a Sr. AI Forward Deployment Engineer to help banking and financial services clients move from AI experimentation to secure, scalable, and measurable enterprise adoption. This senior, client facing role combines Generative AI strategy, AI native software engineering, solution architecture, hands on prototyping, transformation consulting, and executive advisory. Assist in the translation of emerging GenAI capabilities and market trends into practical banking use cases, and present compelling recommendations to senior client executives, including CXO, EVP, and SVP stakeholders.

This role requires a strong combination of technical expertise, banking industry knowledge, strategic thinking, and executive level communication skills. The successful candidate will work with business and technology leaders to define AI transformation priorities, develop differentiated Points of View, identify high value GenAI and Agentic AI opportunities, and translate emerging capabilities into practical solutions and implementation roadmaps. The role requires the ability to operate across strategy, architecture, engineering, governance, adoption, and business value realization. The ideal candidate will influence key client decisions, identify high value AI opportunities, and help drive the adoption of GenAI enabled solutions across the banking enterprise., 1.GenAI Transformation Strategy, Innovation, and Engineering Leadership

. Represent CGI as a senior AI practitioner in client engagements, workshops, demos, and executive conversations.

. Develop compelling Points of View, whitepapers, executive narratives, and thought leadership content on Generative AI, Agentic AI, Responsible AI, and AI enabled modernization in banking.

. Monitor advances in large language models, multimodal AI, autonomous agents, AI platforms, and related technologies, and assess their potential impact on banking operations and business models.

. Work directly with client business and technology leaders to identify where AI can create meaningful operational, financial, customer, software delivery, or mission impact.

. Shape differentiated GenAI positioning and value propositions to support CGI's account growth and client engagement strategies.

. Demonstrate curiosity and a strong willingness to experiment with new AI technologies, tools, and approaches as the industry evolves.

. Provide technical leadership across prompt engineering, model orchestration, vector databases, evaluation frameworks, AI observability, MLOps/LLMOps, agent orchestration, context engineering, and responsible AI controls.

2.Banking Use Case Ideation and Solution Definition

. Identify and prioritize high value GenAI and Agentic AI use cases across banking areas, including: Retail and Commercial Banking Lending, Payments, and Treasury Risk, Compliance, AML, and Fraud Customer Service, Technology, and Operations

. Translate complex business challenges into practical AI solution concepts, target state architectures, implementation roadmaps, and measurable business outcomes.

. Evaluate use cases based on value, feasibility, data readiness, risk, regulatory considerations, and implementation complexity.

. Collaborate with enterprise architects, banking domain experts, data scientists, engineers, and delivery teams to validate solution feasibility and define scalable approaches.

. Support the development of prototypes, proofs of concept, demonstrations, and reusable AI solution assets.

3.Client and Executive Engagement

. Present GenAI Points of View, demonstrations, solution concepts, and transformation recommendations to senior banking executives, including CXO, EVP, and SVP stakeholders.

. Lead client workshops, discovery sessions, innovation forums, ideation sessions, and executive briefings.

. Facilitate discussions that connect emerging AI capabilities to specific client priorities and business challenges.

. Clearly articulate the business value, implementation considerations, governance requirements, risks, and expected return on investment associated with GenAI adoption.

. Build trusted relationships with business and technology leaders and influence strategic decisions related to AI transformation.

4.Thought Leadership and Capability Development

. Partner with CGI sales, account, consulting, and delivery leadership to support strategic client pursuits and account growth.

. Contribute to RFP responses, proposals, solution shaping activities, executive presentations, and business cases.

. Develop differentiated GenAI solution narratives that reflect the client's business priorities, regulatory environment, and technology landscape.

. Advise client stakeholders on GenAI strategy, operating models, governance, adoption roadmaps, and responsible implementation.

. Help transition strategic ideas and proof of concept initiatives into scalable, production ready solutions.


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