AI Applied Engineer - Bangalore

• Take ambiguous workflow requests and turn them into scoped, architected, implemented, and deployed multi-agent systems
• Build reliable multi-step, multi-agent workflows used in production by financial institutions
• Own reliability, latency, success metrics, and customer adoption
• Work directly with customer engineering teams to deliver smooth deployments
• Convert bespoke workflows into reusable platform primitives and components
• Build orchestration logic, tools, templates, and pipelines used across engineering pods
• Ship V1s in days, operate with high agency, tight prioritisation, and strong defaults
• Identify patterns across customers and turn them into reusable systems
• Influence architecture and direction of core platform components
• Use AI for coding, testing, debugging, workflow design, and documentation
• Build evals, safety nets, and AI-native engineering workflows

Must-Haves

• 4+ years of software development in fast-paced, product-focused environments
• Owned a subsystem or workflow end-to-end (requirements architecture implementation launch)
• Strong Python fundamentals; think in primitives, patterns, and systems
• Already use AI to automate work or build LLM-powered workflows
• Comfortable translating customer ambiguity into crisp technical solutions
• Able to unblock yourself through learning, experimentation, and AI tools
• Thrive under tight deadlines, high expectations, and minimal process
• Youll have a solid grasp of our tech stack: Python, React / NextJS, Fast API, MongoDB, Redis

Nice-to-Haves

• Built or orchestrated multi-step LLM or agentic workflows
• Experience with financial workflows (credit, investment, ESG, risk)
• Infra/ops exposure (Kubernetes, Terraform, Azure/AWS, CI/CD, observability)
• Experience at early-stage startups
• Built internal frameworks, tooling, or templates used by multiple teams
• Experience with evals, guardrails, or workflow orchestration systems

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