Job Summary

Forward Deployment Engineer responsible for designing, deploying, and scaling AI-driven enterprise solutions using modern full-stack technologies. The role combines hands-on development (Java, Spring Boot, Angular) with applied AI/ML integration, focusing on rapid solution delivery, productionization of AI models, and close collaboration with business stakeholders in an Agile environment.

Key Responsibilities

AI Solution Deployment & Integration

• Design and deploy AI-enabled solutions (LLMs, ML models, intelligent APIs) into enterprise systems
• Integrate AI/ML services (Azure AI, OpenAI, or similar) into microservices architecture
• Implement prompt engineering, orchestration logic, and AI workflow pipelines for business use cases
• Translate business problems into scalable AI-driven solutions in collaboration with stakeholders

Full Stack Engineering

• Develop and enhance microservices-based applications using Java and Spring Boot
• Build intuitive and responsive UI using Angular, including AI-driven interfaces
• Design and implement AI-enabled REST APIs aligned with enterprise integration patterns
• Ensure high-performance, scalable, and secure system design

Automation & Engineering Excellence

• Develop automated test frameworks covering application and AI workflows (functional + model validation)
• Ensure code quality through reviews, static analysis, and automation-first principles
• Embed AI-assisted development practices (e.g., code copilots, auto-testing, intelligent debugging)

DevOps & Cloud Deployment

• Enable continuous integration and deployment across environments
• Deploy and manage applications in cloud-native environments (Azure/Kubernetes)
• Implement containerization and scalable deployment strategies for AI services

Stakeholder Engagement & Agile Delivery

• Work directly with business teams to rapidly prototype and deploy AI use cases
• Participate in Agile ceremonies and deliver high-impact sprint outcomes
• Troubleshoot production issues and optimize deployed AI solutions based on usage patterns

Skill Requirements

Technical Skills Required

Core Engineering

• Strong experience in Java, Spring Boot (Microservices Architecture)
• Hands-on experience with Angular or modern front-end frameworks
• Expertise in building and consuming RESTful APIs
• Strong knowledge of SQL Server / relational databases

AI & Data Engineering

• Experience integrating AI/ML services (Azure AI, OpenAI APIs, or similar)
• Understanding of LLMs, prompt engineering, embeddings, and vector databases
• Familiarity with AI orchestration frameworks (LangChain, Semantic Kernel, etc.) – good to have
• Exposure to data pipelines and feature engineering concepts

Testing & Automation

• Experience with Junit and modern test automation practices
• Exposure to API testing and AI workflow validation
• Experience in UI automation (Selenium or equivalent)
• Understanding of integrating test automation into CI/CD pipelines

CI/CD & MLOps

• Hands-on experience with CI/CD tools (Azure DevOps, Jenkins, GitHub Actions)
• Understanding of AI model deployment pipelines and versioning
• Familiarity with Docker, Kubernetes, and cloud-native deployments
• Strong knowledge of Git and branching strategies

Preferred / Good to Have

• Experience in large-scale enterprise transformations or government programs
• Familiarity with data governance, AI ethics, and responsible AI practices

Other Requirements

Other Requirements

Soft Skills

• Strong communication skills with ability to bridge business and technical teams
• Experience working in distributed teams (IST/EST collaboration)
• Strong ownership mindset with focus on outcome-driven delivery
• Adaptability to evolving AI landscape and business priorities
• Ability to work in high-impact, fast-paced deployment environments