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# Senior Forward Deployed Engineer

- **Company:** Cotiviti, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Architectural Patterns, Microsoft Azure, Information Engineering, Python (Programming Language), Machine Learning, Open Source Technology, Rapid Prototyping Process, Software Deployment, Software Engineering, Web Application Frameworks, Pinecone, Cloud Platform System, LangChain, Retrieval-Augmented Generation, Large Language Models, Fastapi, Containerization, Weaviate, Machine Learning Operations, FAISS, Virtual Agents, Api Design, Docker, Databricks
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-forward-deployed-engineer-austin-tx--074c6938-72ce-4423-9938-f9983cd875db

## About the Role

Use Cases, Software Agents, Machine Learning, Artificial Intelligence (AI), Systems Scalability, Engineering, Embedded Systems, Consulting, Technical Leadership, Customer Relations, This is an ideal role for someone who thrives in ambiguous environments, enjoys solving hard real-world problems with code, and wants to shape the future of AI in enterprise., * 5-8+ years of software engineering experience, with at least 3+ years in AI/ML-focused roles.

 * Demonstrated experience leading technical delivery in a client-facing or consulting environment.
 * Strong understanding of modern AI architectures, including experience deploying LLMs, building RAG pipelines, and working with vector databases (e.g., Pinecone, Weaviate, FAISS).
 * Fluency in Python, with experience in cloud platforms (AWS, GCP, or Azure), containerization, and scalable API design.
 * Excellent interpersonal and communication skills; able to command technical and business conversations with senior stakeholders., * Experience in regulated or high-complexity environments (e.g., finance, healthcare, legal, government).
 * Familiarity with enterprise AI lifecycle tools (e.g., MLflow, Ray, Databricks, Airflow).
 * Contributions to open-source AI tools or internal frameworks in previous roles.
 * Willingness to travel for key client engagements (if applicable).

## Description

We are hiring a Senior Forward Deployed Engineer (FDE) to lead complex, client-facing AI engineering projects. This role blends deep technical expertise with high-level consulting skills: you'll be responsible for scoping, designing, and delivering mission-critical AI solutions, while guiding clients through technical and strategic decision-making. You'll act as both a trusted advisor and a hands-on technical leader, embedded directly with client teams to ensure the successful deployment and adoption of AI technologies., * Lead architecture and design of AI/ML solutions tailored to unique client requirements, balancing scalability, performance, and maintainability.

 * Guide clients through decisions related to LLM integration, data engineering, infrastructure design, and model operations.
 * Own end-to-end solution delivery, from exploration and rapid prototyping to production deployment and handoff.

2. Client Engagement & Consulting

 * Serve as the senior technical point of contact during client engagements-trusted by executives, product leaders, and technical teams alike.
 * Conduct technical discovery, shape implementation roadmaps, and communicate risks and trade-offs clearly to diverse stakeholders.
 * Influence long-term client strategy through technical advisory, architectural reviews, and enablement sessions.

3. Deep AI Engineering

 * Build AI-driven applications using modern frameworks and tools (e.g., Python, LangChain, FastAPI, Docker, cloud-native platforms).
 * Design and implement workflows involving generative AI (e.g., retrieval-augmented generation, prompt tuning, embeddings pipelines).
 * Collaborate with internal research, data, and platform teams to extend company-wide best practices to client-specific contexts.

4. Mentorship & Technical Enablement

 * Mentor junior engineers and consultants across engagements, fostering a high bar for technical quality and client service.
 * Help define internal tooling, architecture patterns, and deployment playbooks based on field experience.
 * Represent the engineering team in pre-sales discussions, project scoping, and high-stakes strategic planning.