AI Engineer

About the role

A fast-growing enterprise AI company is looking for a Senior Forward Deployed Engineer to take technical ownership of strategic AI solution deployments for enterprise customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership, with a focus on building customer-specific applications on an Agentic AI platform.

You will lead the architecture, prototyping, implementation, and post-deployment optimization of large-scale Agentic and Knowledge AI solutions. The role involves working across enterprise data pipelines, multi-agent orchestration, RAG workflows, SLM fine-tuning, platform customization, full-stack delivery, and production-grade AI systems. You will collaborate closely with customers, Product, Platform Engineering, and cross-functional teams to translate ambiguous business needs into scalable engineering plans and successful deployments.

Responsibilities

• Lead the architecture, prototyping, implementation, and post-deployment optimization of large-scale Agentic and Knowledge AI solutions
• Work across enterprise data pipelines, multi-agent orchestration, RAG workflows, SLM fine-tuning, platform customization, full-stack delivery, and production-grade AI systems
• Collaborate with customers, Product, Platform Engineering, and cross-functional teams to translate ambiguous business needs into scalable engineering plans
• Design and implement enterprise data pipelines and system integrations
• Customize platform components, integrate APIs, build reusable tooling, or extend platform logic
• Ensure observability, monitoring, versioning, telemetry, and trustworthy AI deployment practices
• Mentor and communicate effectively with technical and business stakeholders

Requirements

• 10+ 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 AI/ML, data-intensive, or enterprise-grade applications in production
• Strong full-stack development experience with Python, Node.js or Go, and React or Vue
• DevOps experience with Docker, Kubernetes, CI/CD, and modern cloud-based deployment practices
• Strong knowledge of REST APIs, Python, SQL, GraphQL, Webhooks, and enterprise integration patterns
• Solid understanding of LLMs, prompt engineering, prompt tuning, vector databases, RAG pipelines, and agentic workflows
• Experience with vector databases such as AstraDB, Pinecone, or Weaviate
• Familiarity with RAG frameworks such as LlamaIndex or Haystack
• Experience with agent and workflow orchestration tools such as LangChain, LangGraph, or CrewAI
• Ability to lead technical solution design and implementation for strategic enterprise customers
• Strong project ownership and collaboration skills across technical and business stakeholders
• Undergraduate degree, master’s degree, or PhD in Computer Science, Data Science, or a related technical field

Skills

• Multi-agent orchestration
• LLM workflows
• RAG workflows
• SLM fine-tuning
• Python
• Docker
• Kubernetes
• CI/CD
• GraphQL

Bonus Skills

• Knowledge of SLM fine-tuning, model distillation, and model optimization techniques
• Experience building and delivering enterprise Agentic AI solutions
• Experience working with Agentic development platforms
• Familiarity with graph databases, multimodal AI systems, evaluation frameworks, security, guardrails, and GPU infrastructure trends
• Experience contributing to reusable assets, technical best practices, internal frameworks, and documentation
• Prior experience supporting post-deployment optimization and production adoption for enterprise customers
• Experience partnering with Product and Platform Engineering teams to identify feature gaps, customer pain points, and product improvement opportunities