Agentic AI Engineer

AiMi Technologies AB

IndiaremotePosted 1 month ago

Skill Required

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Key highlights

3+ years of hands‑on development experience required.
Solid back‑end development experience in Node.js required.
Hands‑on experience building production‑grade agentic AI in a live financial markets platform.
Remote‑first team culture.
Opportunity to influence architectural decisions early in a fast‑moving startup.

Role overview

Join AiMi and build the future of Capital Markets Infrastructure. At AiMi, we are revolutionising the management of critical trading and market data infrastructure through AI-driven automation, replacing manual, static processes with dynamic, data‑driven workflows that enable organisations to achieve greater efficiency, agility, and control. We operate at the cutting edge of agentic AI, deploying autonomous agents that ingest venue and vendor notifications, assess impact across client infrastructure, and drive change‑management workflows in real time.

Responsibilities

Build and ship new features and functionality that directly serve our clients across back‑end services, agentic workflows, and integrations that power the platform.
Contribute to the development and continuous improvement of our agentic AI pipeline, translating complex capital markets workflows into reliable, production‑grade agent behaviour.
Design, build, and maintain skills, connectors, and MCP‑based integrations that extend the capabilities of AiMi agents – connecting to client systems, internal tooling, and third‑party platforms.
Contribute to agent evaluation – designing and running evaluations that assess agent accuracy, reliability, and behaviour across real‑world workflows, and using those insights to drive continuous improvement.
Build and maintain production observability and alerting across the agent pipeline, including monitors for agent latency, error rates, failed workflows, and unusual failure patterns, integrated with team paging/notification workflows.
Build resilient agent and streaming workflows, including appropriate timeouts, failure handling, retries, circuit breakers, fail‑fast behaviour, and recovery patterns for long‑running LLM, agent, and SSE‑based calls.
Diagnose dependency and version conflicts in Node.js/npm monorepos, including package resolution, transitive dependencies, lockfiles, and runtime issues.
Participate in agentic SDLC practices: spec‑driven development as part of day‑to‑day engineering workflow.
Build and maintain robust back‑end services, container and serverless‑based services and APIs in Node.js, with a working understanding of our React/TypeScript front‑end codebase.
Work across the full stack – React/TypeScript front‑end, Node.js back‑end services, and AWS Lambda – to deliver well‑tested, maintainable code and scalable services.

Requirements

3+ years of hands‑on development experience.
Solid back‑end development experience in Node.js, with experience building and consuming RESTful APIs.
Practical experience working with LLMs, agent frameworks, or AI automation tooling: Mastra, LangChain, LlamaIndex, Claude, OpenAI or similar.
Familiarity with agentic SDLC practices and spec‑driven development workflows (Claude Code, Cursor, CodeRabbit, or similar).
Working knowledge of AWS cloud services – Lambda, Bedrock, DynamoDB, S3, Cognito, API Gateway, CloudWatch.
Experience with MongoDB and DynamoDB (or equivalent NoSQL databases).
Solid understanding of event‑driven architecture patterns.
Comfortable with testing at multiple levels – unit, integration, and E2E – and a genuine commitment to developer‑led testing approaches.
Familiarity with CI/CD workflows, GitHub Actions, and version control best practices.
A pragmatic, ownership‑driven mindset with the ability to work independently in a remote, fast‑paced environment.
Clear written communication skills – important for async collaboration and for working within our spec‑driven development process.

Nice to have

Domain knowledge in capital markets, trading infrastructure, market data, or financial services.
Experience with LLM observability tooling such as Langfuse, Helicone, or similar.
Familiarity with streaming architectures and server‑sent events (SSE).
Exposure to PostHog or other feature flag and analytics tooling.

Benefits

Hands‑on experience building and shipping production‑grade agentic AI in a live financial markets platform.
Deep exposure to modern AI engineering, LLM evaluation, agent observability, prompt engineering, and agentic SDLC practices as part of daily work.
Direct involvement in architectural decisions at an early‑stage, fast‑moving startup with real, visible impact.
Practical insight into capital markets infrastructure and trading operations.
Opportunity to grow into a senior or lead engineering role as AiMi grows.
Collaborative, remote‑first team culture with a strong engineering discipline.