Experience:

• 3-5 years of hands-on software engineering experience
• Experience building production-grade applications using Python and TypeScript
• Proven experience developing, deploying, and operating AI-powered applications or large language model solutions in production
• Experience integrating intelligent automation with enterprise systems
• Experience working with data platforms, data lakes, vector databases, or distributed data architectures
• Experience with evaluation methodologies, testing strategies, observability, and monitoring for AI systems
• Experience with modern software engineering practices including Git, CI/CD, Docker, and cloud-native deployments
• Experience working within regulated industries such as fintech, financial services, banking, trading, or brokerage environments

Responsibilities:

• Design, build, deploy, and optimize production-grade AI agents automating operational and customer workflows
• Own complete agent lifecycle from architecture to production deployment and monitoring
• Develop maintainable Python and TypeScript solutions for autonomous decision-making and multi-step workflows
• Integrate AI agents with CRM, ticketing, onboarding, payment, trading, and data platforms
• Build and maintain MCP servers, custom tools, and integration layers
• Implement evaluation frameworks, testing, observability, audit trails, and governance controls
• Design human-in-the-loop workflows and security guardrails aligned with financial regulatory requirements
• Collaborate with Client Experience, Compliance, Product, Data Analytics, QA, and Engineering teams
• Champion AI adoption through technical demos, workshops, and enablement sessions
• Continuously evaluate emerging AI models and frameworks to improve platform capabilities
• Monitor production systems for model drift, optimize performance, and ensure long-term health of AI agents

Additional responsibilities:

• Translate ambiguous business challenges into scalable technical solutions
• Operate independently while influencing multiple cross-functional teams globally
• Ensure safe and compliant AI operations
• Maintain transparent decision-making processes

Nice to have:

• Experience with agentic architectures, tool-calling frameworks, orchestration patterns
• Experience with Model Context Protocol or similar integration standards
• Strong analytical and problem-solving skills
• Excellent communication and stakeholder management skills

More skills:

Python, TypeScript, AI-powered applications, Model Context Protocol (MCP), Enterprise platform integration, Salesforce, DevRev, Customer support platforms, Distributed data architectures, Evaluation methodologies, Testing strategies, Observability tooling, Monitoring frameworks, Git, CI/CD pipelines, Docker, Cloud-native deployments, Distributed systems, Scalable application architectures, AI governance, Auditability, Security controls, Privacy requirements, Human-in-the-loop operational models

Other:

• Competitive compensation package
• Learning and development programs, training resources, and certification support
• 18 days annual leave plus 12 days sick leave
• Local public holidays
• Comprehensive health insurance benefits
• Interview process includes TA interview, hiring manager discussion, live coding and prompt engineering assessment, agentic system design interview, and architecture deep dive
• Employment eligibility restricted to candidates with appropriate rights and documentation for employment in India
• Commitment to fairness, respect, inclusion, and equal opportunity in the workplace
• No unsolicited resumes accepted from recruitment agencies without prior written consent