Senior Forward Deployed Engineer – Agentic AI / RAG
Job Type
- Contract – 6+ Months
Location
- Texas – Remote
- Candidates must currently reside in Texas and be available for up to 25% travel for customer engagements.
- Visa US Citizens Only
Experience
- 15+ Years Overall Experience
Pay Rate
- $63/hr on W2 | $70/hr on C2C
Job Description
We are seeking a Senior Forward Deployed Engineer to take technical ownership of strategic enterprise AI deployments. This role combines hands-on software engineering, solution architecture, customer engagement, and delivery leadership, with a strong focus on Agentic AI, RAG, enterprise integrations, and production-grade AI systems.
The ideal candidate will have extensive experience designing, building, deploying, and optimizing enterprise AI solutions while working directly with customers and technical stakeholders.
Key Responsibilities
- Lead architecture, prototyping, implementation, and post-deployment optimization of enterprise AI solutions.
- Design and implement Agentic AI and RAG-based applications.
- Build and orchestrate multi-agent workflows using modern agent frameworks.
- Develop production-grade AI applications using Python and modern full-stack technologies.
- Design enterprise data pipelines, APIs, integrations, and knowledge systems.
- Work with LLMs, prompt engineering, prompt tuning, vector databases, and RAG pipelines.
- Deploy and operate solutions using Docker, Kubernetes, and CI/CD.
- Develop integrations using REST APIs, GraphQL, Webhooks, SQL, and enterprise integration patterns.
- Customize platform components, APIs, reusable tooling, and platform logic.
- Partner directly with customers to understand ambiguous business requirements and translate them into actionable technical solutions.
- Collaborate with Product, Platform Engineering, and cross-functional teams to address customer needs and product gaps.
- Establish observability, monitoring, telemetry, versioning, and trustworthy AI practices.
- Support production adoption, troubleshooting, optimization, and ongoing customer success.
- Mentor engineers and contribute to reusable frameworks, best practices, and technical documentation.
Required Skills
- 10+ years of software/engineering experience
- At least 2 years of customer-facing, field engineering, solutions engineering, or forward deployed engineering experience
- Strong production experience building AI/ML, data-intensive, or enterprise applications
- Strong Python development
- Experience with Node.js or Go
- Experience with React or Vue
- Strong understanding of LLMs and Generative AI
- Experience with RAG workflows
- Experience with multi-agent orchestration / agentic workflows
- Prompt engineering and prompt tuning
- Experience with vector databases such as Pinecone, Weaviate, or AstraDB
- Experience with LlamaIndex or Haystack
- Experience with LangChain, LangGraph, or CrewAI
- Strong Docker and Kubernetes experience
- CI/CD and modern cloud deployment practices
- REST APIs, GraphQL, Webhooks, SQL
- Enterprise data pipelines and system integrations
- Strong solution architecture and technical design skills
- Experience with observability, monitoring, telemetry, and production systems
- Excellent customer communication and stakeholder management skills
- Bachelor's, Master's, or PhD in Computer Science, Data Science, or related technical field
Preferred / Bonus Skills
- SLM fine-tuning
- Model distillation and optimization
- Enterprise Agentic AI implementations
- Agentic development platforms
- Graph databases
- Multimodal AI
- AI evaluation frameworks
- AI security and guardrails
- GPU infrastructure
- Reusable AI frameworks and internal tooling
- Post-deployment AI optimization
- Experience partnering with Product and Platform Engineering teams
Additional Requirements
- Must currently reside in Texas
- US Citizens only
- Must be comfortable with up to 25% travel
- Must be available for remote customer engagements
- Strong customer-facing communication and presentation skills required
Interview Process
- Screening with Turing HR + Technical screening with Turing + 2 rounds with the Client
Must Haves
- Multi-agent orchestration, LLM, RAG workflows, SLM fine-tuning, Python, Docker, Kubernetes, CI/CD, GraphQL