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Tech Lead

Tech Lead

LatentBridge
8-12 Years
Early Applicant
  • Posted 9 days ago
  • Be among the first 10 applicants

Job Description

• 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
• Experience working in Agile delivery environments
• 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

More Info

Job Type:
Industry:
Employment Type:

Key Skills

Anthropic Claude

API-based integration

Google Gemini

AI ML GenAI

vector databases

event-driven asynchronous processing

Azure OpenAI

CI CD

LangGraph

enterprise authentication

LangChain

LLMs

NoSQL databases

Semantic Kernel

data ingestion and transformation pipelines

OpenAI

LlamaIndex

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