AI Developer + Java

Required Qualifications & Expertise

• Senior/Lead Engineering Track Record: Proven experience in a senior or lead software engineering capacity, with demonstrated success guiding technical projects and mentoring teams.
• Core Programming: Deep expertise in Python and its ML/AI ecosystem. Familiarity with Java for middleware and enterprise integrations is a plus.
• AI/ML & LLM Mastery:
  • Expert understanding of LLM architectures, deep learning, NLP, and hands-on experience fine-tuning models on domain-specific data.
  • Practical mastery of RAG, advanced prompt engineering, and designing agentic architectures.
• Data & Middleware Systems: Hands-on experience with relational databases (PostgreSQL), Vector Databases, key-value stores (Redis), and Pub/Sub event messaging.
• Software Architecture: Strong command of microservices, REST/gRPC API design, concurrency models, and observability.
• Cloud & DevOps: Proficiency with Azure and/or GCP, containerization (Docker, Kubernetes), and modern CI/CD pipelines (e.g., Azure DevOps, GCP Cloud Build, Jenkins).
• Quality & Practices: Strong commitment to engineering excellence with practical experience in TDD, BDD, and automated testing.
• Communication Skills: Exceptional verbal and written English communication and presentation skills, capable of influencing cross-functional stakeholders at all levels.

We are seeking a Lead AI/ML & Software Engineer to spearhead the technical design, execution, and deployment of flagship AI initiatives. In this role, you will lead the architecture of scalable ML systems, write high-quality code, and mentor engineering teams. Positioned at the intersection of enterprise software development, modern generative AI (LLMs, RAG, Agentic Architectures), and cloud platform engineering, you will bridge the gap between complex business requirements and cutting-edge, production-ready AI solutions.

,[Technical Leadership & Strategy, Architectural Ownership: Lead the technical design, execution, and production deployment of core AI/ML systems and flagship platform capabilities., Technology Innovation: Co-drive long-term technical strategy by prototyping advanced RAG pipelines, agentic workflows, LLM fine-tuning, and model optimization techniques., Engineering Standards: Establish and champion coding standards, testing methodologies, and responsible AI best practices (ensuring model fairness, transparency, and governance)., Team Mentorship: Guide, unblock, and elevate fellow engineers, fostering a culture of technical excellence and continuous improvement., Software & AI Systems Engineering, Exemplary Code Quality: Design, write, and maintain robust, testable, reusable, and well-documented production code., Advanced Generative AI Delivery: Build sophisticated Retrieval-Augmented Generation (RAG) systems, vector database integrations, and intelligent agents to unlock value from complex financial datasets., Stakeholder Alignment: Translate complex business objectives into actionable technical architecture, effectively communicating technical strategies to both technical teams and business leaders.] Requirements: AI, Python, ML, LLM, Deep learning, NLP, RAG, Relational database, PostgreSQL, Redis, PUB, Microservices, REST API, gRPC, API, Cloud, Azure, GCP, Docker, Kubernetes, CI/CD Pipelines, Azure DevOps, Jenkins, TDD, BDD, Automated testing, Java