Forward Deployment Engineer (FDE) Technical Lead - Artificial Intelligence

ClifyX; Santa Clara (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

ClifyX seeks a Forward Deployment Engineer (FDE) Technical Lead to engineer AI-enabled solutions and lead end-to-end deployments. You will work with customer stakeholders, architects and teams to define technical approaches, rapidly develop prototypes and guide integration into production environments.

The role requires hands-on coding, architectural design of APIs and data flows, and leadership across software, AI, data, cloud, and platform technologies to ensure scalable, secure delivery.

Qualifications

• Bachelor's or Master's degree in computer science or related field.
• Experience developing backend services, APIs, and distributed applications.
• Experience processing and transforming structured and/or unstructured data.
• Hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
• Experience in Git, testing frameworks, code reviews and modern software engineering practices.
• Strong debugging and troubleshooting capabilities.
• Hands-on exposure to large language models and generative AI application development.
• LLM APIs and model integration.
• Prompt engineering and structured outputs.
• Embeddings and vector search/vector databases.
• Understanding AI application performance, security and cost considerations.
• Integration of AI capabilities into enterprise applications.
• Hands-on experience with enterprise GenAI implementations.
• Experience with vector databases such as pgvector, Pinecone, Weaviate, Milvus or similar technologies.
• Experience with frameworks for building AI applications and agents.

Responsibilities

• Design and develop application services, APIs, integrations and AI-enabled solutions.
• Remain hands-on with coding, debugging, code reviews and technical troubleshooting.
• Lead rapid prototyping and Proof-of-Concept development to validate solution approaches.
• Define application architecture, APIs, data flows, integration patterns and deployment approaches.
• Guide engineers across software, AI, data, cloud and platform technologies.
• Review code and ensure engineering quality, security, scalability and maintainability

Skills

Backend services

APIs design

Distributed systems

Cloud platforms

Git & CI

Debugging

GenAI / LLM

Prompt engineering

Vector databases

AI integration

Education

Bachelor's or Master's in CS

Tools

pgvector

Pinecone

Weaviate

Milvus

Job description

Role: Forward Deployment Engineer (FDE) Technical Lead - Artificial Intelligence

Location Options: Santa Clara, CA / Atlanta, GA / Cincinnati, OH / Edison, NJ

Candidates should be comfortable with working onsite at either the client site or Client Office at one of these locations.

Job Description

The Forward Deployment Engineer (FDE) Technical Lead is a hands‑on engineering leader responsible for solving complex problems by combining software engineering, AI/GenAI, data, cloud, integration and platform technologies.

The Technical Lead works directly with customer stakeholders, architects and engineering teams to understand business problems, define the technical approach, rapidly develop prototypes, and lead solutions through engineering integration and production deployment.

Unlike a traditional development lead, the FDE Technical Lead is expected to operate effectively in ambiguous environments, make pragmatic technical decisions, write and review code, troubleshoot complex issues, and take end‑to‑end ownership of customer outcomes.

Key Responsibilities

• Design and develop application services, APIs, integrations and AI-enabled solutions.
• Remain hands‑on with coding, debugging, code reviews and technical troubleshooting.
• Lead rapid prototyping and Proof‑of‑Concept development to validate solution approaches.
• Define application architecture, APIs, data flows, integration patterns and deployment approaches.
• Guide engineers across software, AI, data, cloud and platform technologies.
• Review code and ensure engineering quality, security, scalability and maintainability

Qualifications

• Bachelor's or master's degree in computer science or related field.
• Experience developing backend services, APIs, and distributed applications.
• Experience processing and transforming structured and /or unstructured data.
• Hands‑on experience with at least one major cloud platforms: AWS, Microsoft Azure, or Google Cloud.
• Experience in Git, testing frameworks, code reviews and modern software engineering practices.
• Strong debugging and troubleshooting capabilities.
• Hands‑on exposure to:
• Large Language Models and Generative AI application development.
• LLM APIs and model integration.
• Prompt engineering and structured outputs.
• Embeddings and vector search/vector databases.
• Understanding of AI application performance, security and cost considerations.
• Integration of AI capabilities into enterprise applications.
• Hands‑on experience with enterprise GenAI implementations.
• Experience with vector databases such as pgvector, Pinecone, Weaviate, Milivus or similar technologies.
• Experience with frameworks for building AI applications and agents.