Machine Learning Engineer

Senior AI/ML Engineer – Agentic LLM Systems Full time - Paid

Steps AI is a cutting-edge AI company redefining how enterprises retrieve and act on data through autonomous, agent-powered workflows. Our platform leverages the latest in multi-agent orchestration, RAG, and generative AI to deliver real-time, contextual insights. As we scale our product suite, we're seeking an experienced AI/ML engineer to lead the design and delivery of next-generation agentic LLM solutions.

Design production-grade agent ecosystems featuring robust error-recovery, long-term memory, and dynamic tool integration

Build Multimodal LLM Solutions

Integrate vision, audio, and structured data inputs into unified LLM pipelines

Lead the design of Graph-RAG, Agentic-RAG, and hybrid retrieval architectures for high-accuracy knowledge access

Optimize embedding stores, vector databases (FAISS, Milvus), and reranking strategies

Advance Agent-Building Tooling

Develop LLM-based agents for dynamic tasks using orchestration frameworks

Guide junior engineers on SOLID design, DRY/YAGNI coding, CI/CD pipelines, and peer code reviews

Present architecture reviews, design patterns, and performance benchmarks at team tech-talks

Experience: ≥ 2 years in ML/AI engineering, specifically building and deploying LLM-based systems and RAG pipelines

We will critically evaluate your problem statement understanding, system design, theoretical understanding of LLM techniques/models, hands-on coding experience in GenAI domains, also, the application should take ownership in the tasks assigned to them

LLM Orchestration: Experience in designing, deploying, and orchestrating multi-agent systems using LLM-based agents for dynamic task execution across various tools and platforms using langgraph, langchain, autogen, or llamaindex

Familiarity with tool-calling frameworks, LLM-sandboxing, and how LLMs can interact with external systems (e.g., databases, APIs)

MLOps & Cloud: Production deployments on AWS/Azure/GCP using Docker, Kubernetes, Terraform, CI/CD, and monitoring stacks

Mastery of Chain of Thought (CoT), Tree of Thought (ToT), Graph of Thought (GoT), and self-critique strategies

Software Engineering Rigor: Solid understanding of SOLID principles, version control (Git), unit/integration testing, and code review culture

Excellent at articulating technical solutions to both technical peers and non-technical stakeholders

Contributions to open-source agentic frameworks or active involvement in AI standards bodies

Familiarity with real-time streaming data, event-driven architectures, or Large Scale deployed AI agents

Open Source & Live Projects

Active GitHub portfolio showcasing full-stack applications with AI/ML integration

Open source contributions to web frameworks, AI tools, or developer libraries

Live project demonstrations - must present production applications you've built and deployed

System design for scalable web applications with AI integration

Code quality through GitHub portfolio review and live coding sessions

AI/ML integration capabilities through practical project demonstrations

Competitive salary and equity package with rapid growth potential

Cutting-edge tech stack with latest AI/ML tools and frameworks

Generous learning budget for conferences, courses, and certifications

Fully remote with flexible hours and modern development environment

Open source time - contribute to projects during work hours

Direct mentorship from seasoned engineers and AI researchers

Applications without a comprehensive GitHub portfolio and live project demonstration will not be considered.

Join Steps AI and lead the charge in building the autonomous LLM engines that will power tomorrow's enterprise intelligence.

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