About the role

Forward Deployed AI Engineer connecting business strategy with real-world AI implementation. Building scalable AI solutions and ensuring measurable business value.

Responsibilities

Play a lead technical role in designing and delivering AI-enabled solutions across the enterprise.
Build and deliver AI solutions: Design, build, test, and deploy AI-enabled applications, services, and workflows
Work with LLMs, intelligent agents, and automation frameworks to solve real business problems
Take solutions from prototype to production, ensuring they are reliable and scalable
Own technical design: Lead architecture and design for: LLM integrations
Retrieval-augmented generation (RAG)
Agent workflows and orchestration
API and enterprise system integrations
Ensure solutions are secure, reusable, and aligned with enterprise standards
Define and apply reusable patterns and best practices for AI delivery
Contribute to responsible and governed AI adoption
Ensure solutions are production-ready (testing, monitoring, observability)
Troubleshoot issues, perform root cause analysis, and continuously improve systems
Optimize for performance, cost, reliability, and user experience
Work closely with product, architecture, platform, security, and business stakeholders

Strong experience building scalable, distributed systems
Deep knowledge of: APIs, microservices, and service-based architectures
Cloud-native development (Azure preferred)
CI/CD, containerization, and deployment automation
Experience with event-driven systems, data pipelines and data platforms.
Hands-on experience building LLM-powered applications in production
Strong Experience with: Prompt design and evaluation
Model limitations (hallucination, variability, context constraints)
Agent design and orchestration workflows
Tool/API integrations
RAG and knowledge grounding patterns
Experience across the full lifecycle: Use case definition
Solution design
Integration
Deployment
Monitoring and optimization
Strong understanding of: AI observability (quality, latency, cost) Reliability and system performance
Experience working in regulated environments
Strong awareness of: Data privacy and security
AI governance and controls
Misuse prevention (incl. prompt injection risks)
Auditability and human-in-the-loop safeguards