3 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, build, deploy, monitor, and continuously optimize production-grade AI agents for operational and customer-facing workflows.
- Own the complete AI agent lifecycle from architecture and prototyping through production operation and performance improvement.
- Develop maintainable Python and TypeScript solutions for autonomous decision-making and multi-step workflows.
- Integrate agents with CRM, ticketing, onboarding, payment, trading, and data platforms, including Databricks environments.
- Build and maintain Model Context Protocol servers, custom tools, and enterprise integration layers.
- Implement evaluation frameworks, testing, observability, audit trails, governance controls, security guardrails, and human-in-the-loop workflows.
- Collaborate with Client Experience, Compliance, Product, Data Analytics, QA, and Engineering teams to identify and deliver automation opportunities.
- Conduct technical demonstrations, workshops, and enablement sessions to promote AI adoption.
- Evaluate emerging AI models, frameworks, and agentic architectures and monitor production systems for model drift and performance issues.
Requirements
- 3–5 years of hands-on software engineering experience building production applications with Python and TypeScript.
- Production experience developing, deploying, and operating AI-powered applications, agentic workflows, or large language model solutions.
- Strong knowledge of agentic architectures, tool-calling frameworks, orchestration patterns, and Model Context Protocol or similar standards.
- Experience integrating intelligent automation with enterprise systems such as Salesforce, DevRev, customer support platforms, or workflow tools.
- Hands-on experience with data platforms, data lakes, vector databases, retrieval systems, or distributed data architectures.
- Knowledge of evaluation methodologies, testing strategies, observability practices, and monitoring frameworks for AI systems.
- Expertise in prompt engineering, model optimization, and managing behavioral changes across evolving foundation models.
- Experience with Git-based development workflows, CI/CD pipelines, Docker, and cloud-native deployments.
- Understanding of distributed systems and scalable application architectures.
- Experience in fintech, financial services, banking, trading, or brokerage environments is highly desirable.
- Knowledge of AI governance, auditability, security controls, privacy requirements, and human-in-the-loop operating models.
- Strong analytical, problem-solving, communication, stakeholder management, and cross-functional collaboration skills.
Benefits
- Learning and development programs, training resources, and certification support.
- 18 days of annual leave, 12 days of sick leave, and local public holidays.
- Comprehensive health insurance benefits.
- Candidates must have the appropriate rights and documentation for employment in India.
Tech Stack
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