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Senior Forward Deployed Engineer, Agentic AI & RAG

Braintrust

Remote or Boston, Massachusetts • Today

Full-time

USD 63.00 - 84.00 per hour

Senior Forward Deployed Engineer, Agentic AI & RAG

Braintrust

Remote or Austin, Texas • Today

Full-time

USD 63.00 - 84.00 per hour

Senior Forward Deployed Engineer, Agentic AI & RAG

Braintrust

Remote or San Francisco, California • Today

Full-time

USD 63.00 - 84.00 per hour

Senior Forward Deployed Engineer, Agentic AI & RAG

Braintrust

Remote or New York, New York • Today

Full-time

USD 63.00 - 84.00 per hour

Job Details

Skills

Solution Architecture
Partnership
Collaboration
Leadership
Orchestration
Software Design
Customer Facing
Field Engineering
Machine Learning (ML)
Python
Node.js
React.js
Vue.js
DevOps
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Cloud Computing
SQL
GraphQL
Prompt Engineering
Vector Databases
Workflow
LlamaIndex
LangChain
Computer Science
Data Science
Graph Databases
Evaluation
GPU
Artificial Intelligence
Optimization
Documentation

Solution Architecture
Partnership
Collaboration
Leadership
Orchestration
Software Design
Customer Facing
Field Engineering
Machine Learning (ML)
Python
Node.js
React.js
Vue.js
DevOps
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Cloud Computing
SQL
GraphQL
Prompt Engineering
Vector Databases
Workflow
LlamaIndex
LangChain
Computer Science
Data Science
Graph Databases
Evaluation
GPU
Artificial Intelligence
Optimization
Documentation

Summary

About the Role

Lead the architecture and delivery of production Agentic AI and enterprise knowledge solutions for strategic customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership across complex enterprise environments.

This is a remote U.S. contract role. Texas-based candidates are preferred, and the work requires up to 25% travel for customer engagements.

What You'll Do

Translate ambiguous customer needs into scalable technical plans and successful AI deployments.
Architect, prototype, implement, and optimize customer-specific applications on an Agentic AI platform.
Build enterprise data pipelines, system integrations, multi-agent orchestration, RAG workflows, platform extensions, and production-grade AI services.
Lead technical solution design with customers and partner closely with Product, Platform Engineering, and other cross-functional teams.
Improve post-deployment reliability, observability, performance, adoption, and reusable delivery practices.

Requirements

6+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward-deployed engineering roles.
Proven experience building and deploying production AI/ML, data-intensive, or enterprise-grade applications.
Strong full-stack development experience with Python, Node.js or Go, and React or Vue.
Hands-on DevOps experience with Docker, Kubernetes, CI/CD, and cloud-based deployment practices.
Experience designing enterprise data pipelines, system integrations, REST APIs, SQL, GraphQL, webhooks, and reusable platform tooling.
Strong knowledge of LLMs, prompt engineering and tuning, vector databases, RAG pipelines, and agentic workflows. Relevant tools may include Pinecone, Weaviate, AstraDB, LlamaIndex, Haystack, LangChain, LangGraph, or CrewAI.
Ability to lead strategic customer implementations, translate uncertain business needs into actionable plans, and communicate effectively across technical and business stakeholders.
An undergraduate, master's, or PhD degree in Computer Science, Data Science, or a related technical field.

Preferred Experience

SLM fine-tuning, model distillation, or model optimization.
Enterprise Agentic AI delivery, graph databases, multimodal AI, evaluation frameworks, security and guardrails, or GPU infrastructure.
Production observability, monitoring, versioning, telemetry, trustworthy AI practices, and post-deployment optimization.
Creating reusable technical assets, internal frameworks, documentation, or platform improvements.

Engagement and Selection

This is a full-time contract requiring 40 hours per week during Central Time business hours, with full working-hours overlap. The engagement is expected to begin as soon as possible and continue for at least six months. The selection process includes an initial HR screen, a technical screen, and two client interview rounds.

Compensation

$63-$84 USD per hour.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: vonqfeed2
Position Id: 963241771
Posted 3 hours ago

Fitment

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Job Summary: As a Forward Deployed Engineer FDE) at Rackspace Technology, you will be embedded directly with our most strategic enterprise customers to architect, build, and deploy high-impact AI solutions. This role combines deep technical engineering with business acumen, customer empathy, and end-to-end solution ownership. You become the technical bridge between Rackspace's AI platform capabilities and the customer's most pressing business challenges. You will own the full solution lifecycle

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Job Details

Skills

Solution Architecture
Partnership
Collaboration
Leadership
Orchestration
Software Design
Customer Facing
Field Engineering
Machine Learning (ML)
Python
Node.js
React.js
Vue.js
DevOps
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Cloud Computing
SQL
GraphQL
Prompt Engineering
Vector Databases
Workflow
LlamaIndex
LangChain
Computer Science
Data Science
Graph Databases
Evaluation
GPU
Artificial Intelligence
Optimization
Documentation

Solution Architecture
Partnership
Collaboration
Leadership
Orchestration
Software Design
Customer Facing
Field Engineering
Machine Learning (ML)
Python
Node.js
React.js
Vue.js
DevOps
Docker
Kubernetes
Continuous Integration
Continuous Delivery
Cloud Computing
SQL
GraphQL
Prompt Engineering
Vector Databases
Workflow
LlamaIndex
LangChain
Computer Science
Data Science
Graph Databases
Evaluation
GPU
Artificial Intelligence
Optimization
Documentation

Summary

Translate ambiguous customer needs into scalable technical plans and successful AI deployments.
Architect, prototype, implement, and optimize customer-specific applications on an Agentic AI platform.
Build enterprise data pipelines, system integrations, multi-agent orchestration, RAG workflows, platform extensions, and production-grade AI services.
Lead technical solution design with customers and partner closely with Product, Platform Engineering, and other cross-functional teams.
Improve post-deployment reliability, observability, performance, adoption, and reusable delivery practices.

Requirements

6+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward-deployed engineering roles.
Proven experience building and deploying production AI/ML, data-intensive, or enterprise-grade applications.
Strong full-stack development experience with Python, Node.js or Go, and React or Vue.
Hands-on DevOps experience with Docker, Kubernetes, CI/CD, and cloud-based deployment practices.
Experience designing enterprise data pipelines, system integrations, REST APIs, SQL, GraphQL, webhooks, and reusable platform tooling.
Strong knowledge of LLMs, prompt engineering and tuning, vector databases, RAG pipelines, and agentic workflows. Relevant tools may include Pinecone, Weaviate, AstraDB, LlamaIndex, Haystack, LangChain, LangGraph, or CrewAI.
Ability to lead strategic customer implementations, translate uncertain business needs into actionable plans, and communicate effectively across technical and business stakeholders.
An undergraduate, master's, or PhD degree in Computer Science, Data Science, or a related technical field.

Preferred Experience

SLM fine-tuning, model distillation, or model optimization.
Enterprise Agentic AI delivery, graph databases, multimodal AI, evaluation frameworks, security and guardrails, or GPU infrastructure.
Production observability, monitoring, versioning, telemetry, trustworthy AI practices, and post-deployment optimization.
Creating reusable technical assets, internal frameworks, documentation, or platform improvements.

Dice Id: vonqfeed2
Position Id: 963241771
Posted 3 hours ago

Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

AI FULL STACK DEVELOPER

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Forward Deployed Engineer IV - US

Remote

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USD 132,149.00 per year