InLustro
Website:
inlustro.co
Job details:
Company Description
InLustro is an AI-powered job simulation platform that transforms enterprise workflows into executable environments. We enable companies to validate workforce and AI-agent readiness before deployment into live systems.
Our platform compiles SOPs, tools, and decision logic into stateful simulations with verifiable outcomes, enabling enterprises to assess execution — not just knowledge.
We work with organizations across BFSI, IT services, operations, and engineering, powering hiring, onboarding, and role-transition decisions through high-fidelity simulation infrastructure.
Since 2020, InLustro has partnered with 50+ enterprises and 60+ institutions, impacting 20,000+ learners. We are headquartered in Chennai and backed by Singapore-based investors, with national recognition for innovation in learning and workforce technology.
Role: Artificial Intelligence Engineer (Simulation Systems & Agents)
This is not a modeling-only role.
You will design and build production-grade AI systems that operate inside structured, stateful environments — powering simulations where users (and AI agents) must execute real workflows under constraints.
Your work will sit at the intersection of:
- LLM systems
- decision engines
- workflow orchestration
- tool-integrated environments
You will be responsible for building systems where AI doesn’t just predict — it acts, decides, and is evaluated under real-world conditions.
What You Will Build
- Agentic systems that operate within constrained simulation environments (not open-ended prompts)
- LLM pipelines with grounding, verification, and policy enforcement layers
- Decision engines combining rules, probabilistic reasoning, and model outputs
- Simulation backends (state machines, event logs, replay systems)
- Evaluation systems that score execution based on telemetry, not just outputs
- Tool-integrated workflows (APIs, enterprise systems, sandboxed actions)
Core Responsibilities
Design and implement LLM-driven systems with deterministic constraints
Build multi-step reasoning pipelines (planning → grounding → execution → verification)
Develop stateful simulation architectures (not stateless inference)
Integrate AI models with real or emulated tools/APIs
Create evaluation frameworks to measure decision quality and execution correctness
Optimize systems for latency, reliability, and reproducibility
- Work closely with product and domain teams to convert workflows into executable systems
Required Qualifications
Strong foundation in computer science, data structures, and systems design
Experience building end-to-end AI systems in production (not just notebooks/models)
Hands-on expertise with:
At least one ML/LLM framework (e.g., PyTorch, TensorFlow)
Experience with LLM application patterns:
- RAG systems
- Tool use / function calling
Prompt + system design
Understanding of how to control model behavior (not just train models)
- Ability to design systems that are robust to edge cases and failure modes
Strong Signals (Highly Preferred)
Experience with agent frameworks / multi-agent systems
Familiarity with orchestration tools (e.g., Temporal, Airflow, custom pipelines)
Experience building evaluation or benchmarking systems for AI
Exposure to production infra (APIs, databases, distributed systems)
Understanding of state machines / workflow engines
- Prior work on AI in high-stakes environments (finance, ops, healthcare, etc.)
What This Role Is NOT
Not a pure model training / research role
Not limited to data analysis or dashboarding
- Not prompt tinkering without system-level ownership
Why This Role Matters
Most systems today test intelligence in isolation.
We are building systems that test execution under constraints — the missing layer between:
- training
- and real-world deployment
This is foundational to:
- workforce validation
- AI agent certification
- and decision reliability in enterprise systems
One-Line Summary
If you want to build AI systems that actually operate inside real workflows — not just models that sit outside them — this role is for you.
Click on Apply to know more.