AI Engineer

Job not on LinkedIn

🔥 1 minute ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

Where this job comes from

Posted on Certa.ai's careers page, not through a job board

First seen by Remote Rocketship 1 minute ago

Logo of Certa.ai

Certa.ai

201 - 500 employees

Founded 2017

☁️ SaaS

🤖 Artificial Intelligence

📋 Compliance

SaaS • Artificial Intelligence • Compliance

Certa. ai is an AI-first third-party operating system (TPRM OS) that helps organizations automate and orchestrate third-party risk and compliance workflows across the entire vendor lifecycle. The platform provides intelligent orchestration for onboarding, due diligence, continuous monitoring, screening (sanctions, PEP, adverse media, UBO), KYC/KYB and AML use cases, and broader domains such as information security, financial, reputational, ESG, and supply-chain risks. Certa. ai positions itself as a Gartner Magic Quadrant leader for Third-Party Risk Management Tools and emphasizes evidence-based defensibility, configurable business rules, audit trails, and automatic updates to global compliance requirements.

📋 Description

• Own the agent loop, including step control, planning, retries, error feedback, subagents, and parallel tool calls • Build narrow, well-described, permissioned, and safe tools, MCP servers, and skills for agents operating on customer data • Design agent context using compaction, memory, retrieval-as-a-tool, and methods for processing large enterprise records • Build golden sets, regression suites, and trace-based scoring into CI to evaluate every prompt, model, or harness change • Route across models based on capability, latency, and cost; evaluate new model launches and retune the harness • Build runtime capabilities including durable sessions, sandboxed execution, nested-trace observability, token budgets, and graceful fallbacks • Design backend services end to end, including data models, APIs, storage, and failure modes • Build asynchronous pipelines with queues, workers, retries, idempotency, and backpressure • Optimize systems for scale using caching, batching, indexing, and p95/p99 latency budgets on multi-tenant AWS • Implement tenant isolation, least-privilege access, PII handling, and audit trails • Write design documents, defend technical trade-offs in review, and own services in production • Own a Studio backend service, ship production changes, and join its on-call rotation • Diagnose agent failures from traces and ship fixes that measurably improve task success rates • Ship new agent capabilities or backend services for live customer use with defined target metrics

🎯 Requirements

• 3+ years building production backend systems with strong system design • Experience designing and scaling services under real load • Experience selecting data stores, modeling data, and handling async processing, queues, caching, idempotency, and production failure modes • Python preferred • Shipped at least one LLM agent to real users • Ability to explain an agent's loop, tools, failure modes, and performance metrics • Built evals that changed a product or engineering decision • Strong context and tool design instincts; able to diagnose agent failures by reading traces • Uses coding agents such as Claude Code, Codex, or Cursor as a core part of the workflow • Track record of owning outcomes, selecting metrics, improving them, and reporting results honestly • Nice to have: experience with agent harnesses, frameworks, or orchestration layers; enterprise B2B in regulated domains; founder or founding-engineer experience; LangGraph, Agent SDKs, or Deep Agents

🏖️ Benefits

• Top of market salary plus bonuses and equity • 49 days paid time off • Full benefits • Retirement and wellness plans • Professional development support • Remote workspace setup bonus • Annual company offsites in exciting locations around the world

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