• Develop and maintain web applications using a combination of front-end and back-end technologies. • Design responsive and user-friendly interfaces using modern JavaScript/TypeScript frameworks such as Next.js, React.js or Angular and front-end CSS frameworks like Tailwind and Bootstrap. • Implementing server-side logic and database integration using languages like Node.js, Python, or PHP and database technologies like ORMs, MySQL, MongoDB, or PostgreSQL will be an added advantage. • Write clear and concise documentation for APIs, including usage guides and code examples, to facilitate integration by internal and external developers. Basic understanding of Open API specifications. • Write clean, efficient, and well-documented code following industry best practices and coding standards. • Strong understanding of the Javascript ecosystem and architecture and integrations with popular third-party libraries. • Implement API authentication and authorization mechanisms, such as OAuth, JWT, or API keys, to ensure data security and privacy. • Collaborate with designers, product managers, and other stakeholders to gather requirements and translate them into technical solutions. • Participate in requirement analysis sessions to understand business needs and user requirements. • Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews. • Work closely with Agile teams to deliver software solutions on time and within scope.

• Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. • Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. • Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. • Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). • Optimize models/solutions for performance, scalability, robustness and cost-efficiency. • Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. • Document model design, experiments, data provenance and solution rationale. • Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. • Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results.

• Design, develop, test, deploy, and maintain mobile applications using React Native • Estimate engineering effort and plan implementation of system changes • Shift from manual typing to using AI for feature development • Implement user-friendly UX/UI designs • Maintain documentation for building and deploying apps • Build and deploy to App Store and Google Play • Conduct code reviews and ensure security standards are met • Stay updated with new development trends

• Design and ship production AI systems — multi-agent orchestration, routing, and specialized agents that take a request and carry it through to a reliable outcome. • Automate manual operational work across onboarding, support, exceptions, and document/data understanding — turning processes that take hours or days into seconds. • Build the models behind the decisions — forecasting, prediction, matching/allocation, optimization, and reliability scoring that ground the product in data instead of guesswork, exposed as services the agent layer can call. • Design the learning loop. Instrument decisions and their outcomes so models continuously improve, with the data and evaluation infrastructure to support it. • Own reliability and evaluation. Build the eval harnesses, tracing, observability, and guardrails for complex AI workflows where mistakes carry real operational and financial consequences — and prove a model or agent beats the status quo before it ships. • Make the build-vs-rules calls — know when a model genuinely wins, when an agent is the right tool, and when a simple rule is the smarter answer. • Raise the bar and help the team grow — push our prototyping-to-production pipeline forward and mentor engineers as the AI team scales.