
Remote, India, Nagpur, India
Glitter Technology Ventures Pvt. Ltd. (www.glitterlabs.com) is hiring a AI Engineer - Trading Agents to build AI-native systems at the intersection of Edge AI, Vertical AI, and large-scale software and content generation.
We’re looking for someone who builds production systems, not prototypes.
Someone who can take a problem from ambiguity to architecture to deployment without waiting to be told what to do next.
If you think in systems, care about performance, and take ownership seriously, keep reading.
This is a hands-on, high-ownership engineering role at the intersection of AI systems and financial markets.
You will work directly with founders and core engineering to design and build production-grade agentic systems that power autonomous trading workflows, from market signal ingestion to execution-ready decision pipelines.
With 4+ years of experience, you are expected to:
Operate independently with minimal hand-holding
Make sound architectural decisions under real constraints
Deliver clean, scalable, maintainable systems that handle live market data
We move fast. Deadlines are real. Quality is non-negotiable.
Remote, India
Nagpur, MS, India (local candidates preferred)
We work in person, remote, or hybrid for speed, clarity, and tight feedback loops.
Design and build production-grade agentic AI systems for autonomous trading workflows
Develop multi-agent architectures that ingest market signals, reason over data, and generate actionable outputs
Build and maintain LLM-powered research and analysis pipelines for financial decision support
Architect real-time systems for market data processing, signal generation, and execution integration
Integrate with brokerage APIs, market data providers, and financial data SDKs
Own services end-to-end, design, build, deploy, monitor, and iterate
Collaborate directly with founders on system architecture and technical direction
Build agentic systems that operate reliably under live market conditions, not demo environments
Design and implement multi-agent orchestration frameworks for trading research and signal workflows
Write clean, modular, well-documented code that other engineers can reason about
Ensure performance, latency, and observability across data ingestion and agent decision pipelines
Integrate risk controls, guardrails, and human-in-the-loop checkpoints into agentic workflows
Take full ownership of projects and deliver on deadlines without needing to be chased
Proactively identify bottlenecks and failure modes before they become production incidents
Strong programming skills in Python (required); Go or Rust a strong plus
Solid understanding of:
Agentic AI system design, tool use, memory, planning, orchestration
LLM integration patterns: function calling, structured outputs, retrieval-augmented generation
Backend architecture and distributed systems fundamentals
API design and third-party integration
Experience with:
Multi-agent frameworks, LangGraph, CrewAI, AutoGen, or equivalent
Production LLM deployments and prompt engineering at scale
Real-time or streaming data pipelines (Kafka, Redpanda, or similar)
Database design across SQL and NoSQL
Agentic tooling such as Hermes Agent, DeerFlow, or OpenClaw
Familiarity with:
Financial markets, trading concepts, or brokerage API integrations (Alpaca, Tradier, Interactive Brokers)
Market data providers and financial data normalization
Risk management logic within automated systems
Exposure to cloud platforms (AWS, GCP, or Azure)
Open-source contributions or a strong GitHub profile demonstrating agentic or AI systems work
5+ years of hands-on software engineering experience
Demonstrated experience building and shipping agentic or LLM-powered systems in production
Prior exposure to financial systems, quant workflows, or algorithmic trading is a strong advantage
Experience in startup or fast-paced environments preferred
Track record of owning and delivering end-to-end projects with measurable outcomes
Bachelor's or Master's in Computer Science, Engineering, Mathematics, or a related field
Equivalent practical experience accepted if output is strong, working systems, clean code, and clear technical writing speak louder than credentials
Active engagement with the AI and LLM ecosystem is an expected baseline, not a differentiator
Build at the frontier of AI and financial systems engineering
High ownership from day one, you will design systems, not just implement tickets
Work directly with founders on architecture and product direction
No bureaucracy, no slow approval cycles, no performative process
Real systems, real market data, real users, real impact
The fastest path to deep expertise in agentic AI applied to one of the most demanding domains that exists
Most engineers follow specs. We’re looking for engineers who define them.
If that sounds like you, let’s talk.
Note:
Please answer the questions below using the STAR (Situation, Task, Action, Result) format. Be specific, concise, and quantify impact wherever possible.
We read these responses carefully and use them to understand how you think, execute, and create meaningful outcomes.