Sr. GenAI Engineer

Steps AI · On-Site, Hyderabad, India · Full-Time

About Steps AI

Steps AI is an agentic AI platform that powers customer-facing AI agents for businesses across e-commerce, SaaS, healthcare, real estate, EdTech, and financial services. Our agents go live in under five minutes from a single URL, learn the business by ingesting websites, documents, FAQs, and product catalogs, and deploy across web, messaging, and social channels.

We are profitable, growing fast, and shipping production AI to customers every week.

The Role

We are hiring a GenAI Engineer to own the agentic AI layer of our platform — the brains of every conversation our agents have. You will design and evolve our agent runtime, integrate new tools and channels, advance our retrieval and memory systems, and own end-to-end LLM observability.

This role is AI-focused but not AI-only. You will also contribute to the surrounding backend services and data pipelines that power the AI layer. You will work alongside a peer Software Engineer focused on the platform side; together you will set the technical direction for major product areas.

Resumes will only be reviewed if the application form is completed.

Application form: [hidden]

What You Will OwnAgentic AI Systems (Primary)

Agent runtime & control flow — design and evolve how our agents reason, route, recover, and hand off; build robust patterns for human escalation, partial-state resumption, and graceful tool failure

Persona & behaviour engineering — shape how agents adapt across channels, business verticals, and brand voices; encode domain guardrails, retrieval mandates, and structured-output contracts

Multi-provider LLM orchestration — abstract across leading model providers with per-persona routing, fallbacks, retries, and cost/latency tradeoffs

Tool ecosystem — extend, debug, and ship integrations across CRMs, helpdesks, calendars, productivity suites, e-commerce backends, logistics carriers, messaging platforms, and internal services. A new provider should reach production in days, not weeks

Retrieval & ranking — own the hybrid retrieval stack across vector and lexical signals, including reranking, recall/precision tuning, and ingestion-time quality controls

Memory systems — long-term cross-session memory and short-term per-thread state, with clear contracts between them

Streaming protocols — token-level streaming, intermediate event emission, interruption and resume semantics, and structured terminal events for client integration

Workflow Orchestration & Data Engineering

Long-running workflows for ingestion, crawling, FAQ and Q&A synthesis, product discovery, sentiment work, outbound campaigns, and channel onboarding

Queue & worker design — separation of heavy and light work, concurrency control, retry semantics, and end-to-end tracing

Embedding & indexing pipelines — async batched writes, idempotent reindexing, provider rate-limit safety, and intermediate object-store staging

Document understanding — multi-format parsing, OCR for scanned content, and structured extraction

Web acquisition — adapter-based crawling with rate limiting and resilience; pluggable backends for varied site profiles

Provider-agnostic embedding layer — designed so new embedding models drop in without touching downstream consumers

AI / Backend Integration

You will not throw work over the wall. You will go into the backend stack when needed.

The agent configuration pipeline that turns persona definitions into runnable behaviour

New API endpoints powering AI-driven features — summarisation, FAQ synthesis, recommendation flows, and more

Inbound webhook flows from commerce platforms and messaging providers that drive agent behaviour

The plumbing that ties skill and tool configuration across our service boundaries

You Lead. You Don't Just Code.

Own the AI roadmap for your area and propose what to build next

Mentor and review the work of junior engineers as the team grows

Run weekly architecture reviews with the founders

Defend tradeoffs in writing through RFCs, design docs, and postmortems

Be the on-call escalation point for AI / agent production issues

Set the bar for code quality, testing rigour, and observability across the AI stack

Required Skills

You should have shipped these to production and be able to demonstrate them live:

Agent frameworks Production experience with LangGraph, LangChain, or comparable agent runtimes — tool calling, state machines, checkpointing, streaming, human-in-the-loop

LLM APIs OpenAI, Azure OpenAI, Anthropic, Google Gemini — direct integration and proxying patterns

Vector databases At least one of Milvus, Pinecone, Weaviate, or Qdrant — schema design, dense + sparse retrieval, batched upsert, idempotency

Embeddings & reranking Modern embedding models, dimensionality and quality tradeoffs, cross-encoder reranking

Workflow orchestration Temporal, Airflow, Prefect, or equivalent at production scale

Backend (Python) FastAPI, async I/O, Pydantic, structured logging

Backend (TypeScript) Node or NestJS — comfortable enough to ship full-stack features

Observability LLM tracing (Langfuse or similar), OpenTelemetry, error monitoring

Cloud + DevOps Docker, AWS or GCP, CI/CD, production debugging

Strong Plus

Multimodal model integration — vision and audio

Speech: transcription and streaming synthesis

Layout-aware document AI and advanced structured extraction

Multi-agent patterns beyond single-loop architectures

Advanced retrieval research — late-interaction models, learned sparse retrieval, and similar

Open-source contributions to agent frameworks or vector databases

Published papers, patents, or conference talks in the GenAI / agentic space

Domain expertise in e-commerce, govtech, healthtech, or financial services

Mindset We Hire For

You think like a system architect, not a prompt engineer. Prompt-only "AI engineers" are not the right fit.

You ship rapidly and iterate publicly. A new integration goes from idea to production in days.

You read source code instead of asking Stack Overflow. When a framework behaves unexpectedly, you read its internals.

You measure what you ship. Token usage, latency, retrieval quality, regression rates — all instrumented from day one.

You take ownership of failures. When a customer reports a bad outcome, you trace it through prompt, retrieval, and tool output, then fix the root cause.

You operate well in fast-paced, high-ownership environments. This is not a slow shop.

Qualifications

B.Tech / M.Tech / MS in CS, Software Engineering, AI/ML, or a related field

2+ years of professional engineering experience with a strong production track record

Demonstrable experience shipping agentic AI systems to real users

On-site availability in Hyderabad — every working day, in person, with the team

Compensation

Top-of-market base, calibrated to live demonstration of capability

Meaningful equity for a senior IC role

Direct, no-gatekeeper access to the founders

Full ownership of the AI roadmap within your scope from day one

To Apply

Resumes will only be reviewed if the application form is completed.

Application form: [hidden]

The form takes 5 minutes. Submitting a CV outside the form will not be reviewed. Shortlisted candidates will be contacted within 48 hours of submission.

Steps AI · stepsai.co · Hyderabad, India