Emerging Tech Engineer

Responsibilities

• Design, develop, test, operate and maintain Enterprise AI Agents that demonstrate innovative AI capabilities aligned with PDLC initiatives and drive adoption of AI-enabled development workflows.
• Take full stack ownership by consistently writing production-ready, testable code that scales beyond proof-of-concept stage; implement agentic architectures using modern frameworks (Lang Chain, Lang Graph, Semantic Kernel, Auto Gen, MCP).
• Develop AI-enabled proof‑of‑concepts (PoCs) and rapid prototypes that validate emerging AI platforms, tools, and capabilities; establish reusable patterns and architectural blueprints for enterprise‑scale AI integration.
• Consistently create optimal designs adhering to architectural best practices; consider scalability, reliability, and performance when defining technical designs for AI‑powered systems, including RAG patterns and vector database implementations.
• Perform analysis on failures, propose design changes, and encourage operational improvements; conduct technical experimentation and validation of novel AI approaches, documenting findings and recommendations.
• Conduct code reviews to provide guidance on engineering best practices, compliance with development procedures, and security standards for AI‑enabled applications.
• Accountable for ensuring all aspects of product development follow compliance and security best practices, with particular attention to AI/LLM governance, data handling, and prompt engineering safety.
• Embrace emerging technology opportunities and contribute to establishing best practices in support of the bank's AI and technology transformation; partner with strategic vendors and technology partners to evaluate emerging AI solutions.
• Contribute to a culture of innovation, collaboration and continuous improvement by sharing knowledge through internal innovation programs, hackathons, and cross‑team enablement initiatives.
• Collaborate with onshore and offshore development teams to scale, refine, and operationalize PoC solutions; support the broader adoption of AI‑enabled development tools across multiple teams and business units.
• Review tasks critically and ensure they are appropriately prioritized and sized for incremental delivery; anticipate and communicate blockers and delays before they require escalation.

• Bachelor's degree, or equivalent work experience.
• Five to six years of relevant experience.
• 8+ years of development and architectural experience with strong depth across cloud‑native and distributed systems.
• Expert in Python programming with good understanding of other modern programming languages (Java, C#, Go).
• Experience developing full‑stack applications using React.js, Type Script, and modern frontend frameworks.
• Experience building applications using REST API architecture including Auth Flows, Encryption, Observability, and security best practices.
• Hands‑on experience building and deploying GenAI and Agentic AI Applications using MCP, Lang Chain, Lang Graph, Semantic Kernel, Auto Gen, or Azure AI Foundry.
• Developing solutions using RAG (Retrieval‑Augmented Generation) architecture patterns and vector databases (FAISS, Azure AI Services, Pinecone, etc.).
• Proficiency with Git Hub Copilot and Claude Code for accelerated development; understanding of Copilot Studio and other AI‑enabled developer tools.
• Fundamental understanding of AI/ML models, prompt engineering, and LLM integration patterns including agentic workflows and autonomous agents.
• Knowledge of SDLC processes, CI/CD pipelines, and container orchestration (Kubernetes, Docker); experience with enterprise deployment and scaling practices.
• Experience with code quality, testing frameworks, and observability for production systems.
• Strong communication skills with ability to explain technical concepts to both technical and non‑technical stakeholders.
• Experience working in cross‑functional, distributed teams and collaborating across onshore and offshore development organizations.