Technical Architect - Forward Deployment Engineer AI

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

·Lead technical discovery sessions to understand customer business problems, existing technology landscape, data, applications and constraints.

·Translate customer requirements and business problems into scalable technical solutions.

·Own the end-to-end technical implementation from discovery and prototyping through production deployment. 

·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.

·Diagnose complex application, data, integration, infrastructure and production issues.

·Drive solutions from prototype to production-ready implementation.

·Mentor junior and graduate FDEs and provide technical support and guidance.

·Communicate technical decisions, trade-offs, risks and recommendations clearly to customer stakeholders.

*Qualifications:   

·Bachelor's or master's degree in computer science or related field.

·Strong programming skills in Python, Java/JavaScript, C++ or equivalent.

·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:

oLarge Language Models and Generative AI application development.

oLLM APIs and model integration.

oPrompt engineering and structured outputs.

oRAG architectures.

oEmbeddings and vector search/vector databases.

oUnderstanding of AI application performance, security and cost considerations.

oIntegration of AI capabilities into enterprise applications.

·Understanding of production monitoring, logging and observability. 

Good to Have

·Experience delivering solutions in customer-facing environments.

·Experience leading small Agile engineering teams.

·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.

·Cloud and/or AI certifications.