8–12+ years of overall software engineering experience
3+ years of strong hands-on experience in AI/ML, GenAI or related AI engineering
Strong hands-on Python development
Strong recent hands-on experience building GenAI/LLM-based applications
Strong experience with LLMs, prompt engineering, structured outputs and tool/function calling
Hands-on experience with RAG, embeddings, vector databases, document processing, chunking, retrieval and reranking
Hands-on experience with AI agents and agent orchestration, including multi-step workflows, tool-using agents, memory/state management and human-in-the-loop patterns
Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar frameworks
Good understanding of MCP and emerging standards for connecting AI agents with enterprise systems and tools
Experience with backend development using FastAPI, Flask, Django or similar frameworks
Strong understanding of REST APIs, microservices and distributed application architecture
Experience integrating enterprise applications, databases and third-party APIs
Strong coding, debugging, troubleshooting and performance optimisation skills
Experience owning solution architecture and technical design for enterprise applications
Experience taking solutions from discovery/prototype through development and production deployment
Hands-on exposure to at least one major cloud platform: Azure, AWS or GCP
Experience with Docker, Kubernetes, CI/CD, cloud-native application deployment, API management, logging/monitoring and identity/access management
SQL and relational databases; NoSQL databases; vector databases
Data ingestion and transformation pipelines; API-based integration; event-driven/asynchronous processing
Understanding of enterprise authentication/authorization, data privacy, PII handling and enterprise security requirements
Understanding of secure AI architecture, data protection, prompt/input security, AI guardrails, logging, auditability, monitoring, evaluation, regression testing, scalability and cost management
Experience leading technical teams while continuing to contribute to development
Strong client-facing and communication skills
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Ability to move from Client Problem → Solution Architecture → Technical Design → Team Guidance → Hands-on Coding → Code Review → Deployment → Production Support Good-to-Have Skills
Experience with Azure AI Foundry, AWS Bedrock, Google Vertex AI or similar enterprise AI platforms
Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini or equivalent models
Traditional ML/ML engineering knowledge
LLM evaluation frameworks
AI guardrails and responsible AI
LLM observability and tracing
Model and prompt evaluation
Token, latency and cost optimisation
Experience building enterprise AI accelerators or reusable AI platforms
Experience with multi-agent or agentic AI solutions
Experience modernising existing enterprise applications using AI
Microsoft Fabric or enterprise data platforms
BFSI, financial services or other regulated enterprise environments
AI security and responsible AI practices
Experience supporting technical proposals, estimations and solution presentations
Experience mentoring engineers and building engineering standards or reusable frameworks
Git-based development, branching, pull requests and code reviews
Experience with API management, secrets/configuration management and production troubleshooting Key Responsibilities
Understand business requirements and translate them into the right technical solution
Own overall architecture and technical design of AI, GenAI and agentic AI solutions
Define application architecture, AI/LLM components, APIs, integrations, data flows, security and deployment approach
Evaluate technology and model options based on business need, cost, performance, security and scalability
Create architecture diagrams, technical design documents, API specifications and implementation guidelines
Identify technical risks and drive practical solutions
Actively contribute to coding throughout the project
Build critical modules, prototypes, reusable components and integrations
Develop and integrate LLM applications, RAG pipelines, AI agents and APIs
Support complex coding, integration and performance issues
Conduct code reviews and ensure good engineering practices
Improve code quality, performance, security and maintainability
Lead and guide AI/ML engineers, backend developers and other technical team members
Break solutions into technical work packages and guide implementation
Support estimation, sprint planning and technical task allocation
Track technical progress and address dependencies/blockers
Mentor team members and improve technical capabilities
Review designs and code before higher environments
Ensure technical quality throughout the project
Work closely with Project Managers, Business Analysts, Solution Architects, QA and DevOps teams
Own technical delivery and ensure alignment with agreed architecture
Participate in client discovery and technical workshops
Understand client landscape, integrations, data, security and infrastructure constraints
Explain architecture and technical decisions to technical and business stakeholders
Present solution architecture and technical options during client reviews
Support pre-sales with technical solutioning, estimates, architecture and feasibility assessments
Handle technical questions and challenges during client discussions
Take AI solutions beyond prototype into production, including security, governance, evaluation, monitoring, scalability, performance and cost management something around - Anthropic Claude certifications (particularly CCAF for architects), Microsoft AI-103, AWS Certified Generative AI Developer – Professional. Education / Qualification
Bachelor's or Master's degree in Computer Science, Engineering, Information Technology or a related discipline
Equivalent strong hands-on engineering experience may also be considered
About LatentBridge
IT Services & Consulting71 employeesFounded 2018
AI consultancy and innovation firm delivering custom, governance-aligned automation and AI solutions to regulated enterprises.
