Forward Deployed Engineer

** Forward Deployed Engineer*
* ** Category:
** Software Development/ Engineering

** Main location:
** United States, Louisiana, Lafayette

** Position :
** J

*
* Employment Type:

** Full Time

U.S.

- The best version of me ()

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** Position

Description:

*
* The best version of us starts with You!

We CGI looking for Forward Deployed Engineer. With your expertise, you will work with a high performing team to consult and develop solutions for a major client.

As a Forward Deployed Engineer (FDE), you will embed directly with the client's teams to take proof of concept (PoC) initiatives the client has already shortlisted and turn them into working software: validating technical feasibility, hardening the solution into a Minimum Viable Product (MVP), running a scoped pilot, and then partnering with the client's Enterprise Architecture team to roll the solution out across the organization.

This position is located on-site in Lafayette, LA (Preferred), Bloomfield, CT, Raleigh, NC or in a Hybrid working Model.

** Your future duties and responsibilities:*
* .
Partner in an embedded, on site/hybrid capacity with the client to take ownership of PoCs the client has already shortlisted and approved for further investment.

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Perform technical due diligence on each PoC, assessing architecture, data flows, integration points, and the gap between prototype and production grade software.

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Serve as the primary technical point of contact between the client and CGI, providing regular updates on PoC/MVP/pilot progress, risks, and decisions needed.

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Partner with CGI's AI/solution architects on solutioning: validating technical approach, leveraging reusable accelerators and best practices, and escalating architecture or design decisions as needed.

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Scale validated PoCs into MVPs, building in the engineering rigor (testing, CI/CD, monitoring, security controls) required to support real users.

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Design and execute pilot programs to validate MVPs with a limited user base, gather feedback, and define success criteria and exit conditions.

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Collaborate closely with the client's Enterprise Architecture team to align each solution's target state architecture, technology standards, and governance requirements.

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Develop and execute org wide scaling and rollout plans in partnership with Enterprise Architecture, covering migration approach, integration with existing systems, change management, and knowledge transfer.

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Act as the technical bridge between the client's business/product stakeholders and delivery/engineering teams, translating shortlisted ideas into actionable delivery plans.

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Identify technical risks, dependencies, and reusable platform components across multiple PoC to scale efforts.

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Produce documentation, runbooks, and architecture artifacts to support handoff to steady state operations teams.

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Mentor and support client and delivery teams on best practices for rapid prototyping, MVP engineering, and phased scaling.

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Design, build, and maintain computer vision pipelines that analyze and extract insights from large volumes of images at scale.

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Architect and run AI workloads for both training and inference on cloud platforms such as AWS, Azure, or GCP, optimizing for cost, scalability, and performance.

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Develop automation and tooling using Python for data preprocessing, model training, deployment, and monitoring.

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Collaborate with cross functional teams to translate complex business problems into machine learning solutions that guide prediction and forecasting.

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Address the challenges of building, deploying, and scaling production grade computer vision systems, including data quality, model accuracy, latency, and throughput.

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Monitor model performance in production and implement retraining and continuous improvement (MLOps) workflows.

** Required qualifications to be successful in this role:*
* At least 7+ years of professional software engineering experience in:

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Hands on experience with at least one major cloud platform (AWS, Azure, or GCP) and modern Dev Ops practices.

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Computer vision and deep learning frameworks (e.g., PyTorch, Tensor Flow, OpenCV)

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Building, training, and fine-tuning image processing and deep learning models (classification, detection, segmentation)

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Python for ML development, data processing, and automation

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Running AI/ML workloads for training and inference on AWS, Azure, or GCP (e.g., Sage Maker, Azure ML, Vertex AI)

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Processing and managing large scale (TB scale) datasets and their associated data pipelines

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Building and scaling production ML systems, including MLOps practices such as model deployment, monitoring, and retraining.

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Hands on software/platform engineering experience, including direct experience taking prototypes or PoCs into production.

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Demonstrated experience scaling a PoC into an MVP and carrying it through a pilot to broader production rollout.

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Strong full stack or platform…