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Agent Application Engineer (Backend / Agentic AI) — Level 1
Agent Application Engineer (Backend / Agentic AI) — Level 1
Sentiaflow's logo

Agent Application Engineer (Backend / Agentic AI) — Level 1

Sonal Agarwal's profile picture
Posted by Sonal Agarwal
3 - 8 yrs
₹25L - ₹40L / yr
Remote, Bengaluru (Bangalore), Pune, Delhi, Gurugram, Noida
Skills
LangGraph
Web API
Information architecture
knowledge Graph
Semantic search

About Sentiaflow

Sentiaflow is an AI engineering and IT services company building production-grade agentic AI systems, sitting at the intersection of LLMs and real business operations — data, APIs, permissions, workflow state, human decisions, security, and measurable outcomes. Our initial domain focus is healthcare, particularly clinical trials, where reliability, traceability, and clear human-decision boundaries matter more than a slick demo.

Job Description

As a Level 1 engineer, you'll implement bounded parts of a production agentic workflow under an Agent Captain or senior engineer, connecting models to application services, tools, data sources, and human approval points.

You will:

  • Translate a scoped business workflow into typed inputs, outputs, states, actions, and escalation paths
  • Build backend services and tool integrations (Node.js/TypeScript or Python)
  • Use LLMs only where model judgment adds value; keep rules, validation, authorization, and workflow control in deterministic code
  • Design and validate structured model outputs before they touch downstream systems
  • Handle partial data, tool failures, duplicate events, retries, timeouts, rate limits
  • Add logging, traces, metrics, and decision records for diagnosability
  • Write tests and evaluation cases that check whether the full workflow behaves correctly — not just whether output sounds fluent
  • Protect sensitive data; participate in code, design, and release-readiness reviews
  • Explain implementation trade-offs clearly to engineers and stakeholders

Success in 6 months: own a bounded workflow module end-to-end, integrate models without letting probabilistic output bypass deterministic controls, produce release-ready evaluation evidence, and diagnose cross-boundary failures with less supervision.

Desired Skills

  • Approximately 3–6 years hands-on backend/application engineering experience, with demonstrable hands-on work building agentic systems — not just calling an LLM API from a backend service
  • LangGraph (or comparable agent orchestration framework) experience is required — building multi-step, stateful agent workflows with conditional branching, tool-calling loops, and recovery/retry logic, not a single-prompt wrapper
  • Deep RAG experience, including:
  • Chunking strategy design, embedding model selection, and retrieval evaluation (not just "connected a vector DB")
  • Hybrid search (dense + sparse/keyword), re-ranking, and query rewriting/decomposition
  • Handling retrieval failure modes: irrelevant context, stale data, contradictory sources, citation/grounding accuracy
  • Measuring RAG quality (precision/recall on retrieval, faithfulness/groundedness of generation) — not eyeballing outputs
  • Experience designing agent state machines / workflow graphs: tool selection, planning loops, human-in-the-loop interrupts, checkpointing, and state persistence across long-running workflows
  • Strong programming in JS/TypeScript (preferred), Python, Java, C#, or Go
  • Solid grasp of API design, databases, async processing, auth, testing, deployment
  • Comfort reasoning about state, retries, idempotency, concurrency, permissions, audit trails, failure recovery
  • Real production debugging experience, not just greenfield builds
  • Clear technical communication

We're looking for engineers who've actually built and tuned agentic/RAG systems in production — not those who've only wired together frameworks or prompted an LLM API.


Nice to have: experience with other orchestration frameworks (CrewAI, AutoGen, custom state machines), observability/eval tooling (LangSmith, Langfuse, custom trace pipelines), healthcare or regulated-industry background. Bachelors from IIT or NIT highly preferred.

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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Sentiaflow

Founded :
2012
Type :
Products & Services
Size :
0-20
Stage :
Bootstrapped

About

Sentiaflow is an AI engineering company headquartered in New Delhi, building production-grade AI systems for clients around the world — including Fortune 500 enterprises alongside high-growth startups. We work across finance, healthcare, and technology, helping organizations move beyond AI experimentation into real, reliable, production deployments.


We operate in three ways: embedding dedicated AI engineers directly into client teams, building custom AI solutions end-to-end — including RAG pipelines, LLM integrations, and AI agents — and designing the MLOps infrastructure that keeps these systems running reliably at scale.


Joining Sentiaflow means working on live, client-facing AI systems from day one — not internal prototypes shelved after a demo. Our engineers ship production code for organizations that depend on it, across some of the most demanding industries for AI reliability and compliance.


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Tech stack

skill iconPython
skill iconNodeJS (Node.js)
duckdb
skill iconPostgreSQL
LangGraph
OpenAISDK

Candid answers by the company

What is the location preference of jobs?
Why should I join Sentiaflow ?

Delhi-NCR, Pune or Bangalore

Company social profiles

N/A

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