Full stack developer – react | node.js | saas & ai Jobs – 110 Open Jobs Today

AI Automation Engineer
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PixLap —Dharmapuri, Tamil Nadu
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- Full-time
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Quick apply
fullstack intern
BEXO.AI —Mohali, Punjab
- ₹5,000 - ₹8,000 a month
- Full-time
- Master's degree
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2d
Polyglot AI - Native Full Circle Developer
Zycus —Mumbai, Maharashtra
- Full-time
- Azure
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Senior Automation Engineer
Josys —Bengaluru, Karnataka
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Deputy Director - SWE Application Architect
PepsiCo —Hyderabad, Telangana
- Remote
- Azure
- Doctoral degree
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Systems Development Executive (MIS & Automation)
Institute of NeuroDevelopment —Shobhabazar, Kolkata, West Bengal
- ₹15,000 - ₹25,000 a month
- Full-time
- English
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- Paid time off
- Paid sick time
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10d
Engineering Lead
ANSRSource India —Bengaluru, Karnataka
- Full-time
- Hybrid work
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Saas Architect
Jobin & Jismi —Kerala
- Full-time
- CRM software
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7d
App Dev & Support Engineer III
Conduent Business Services India LLP —Noida, Uttar Pradesh
- Email
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Head of Platform Engineering - Fullstack
Alphastream.ai —Bengaluru, Karnataka
- Email
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PMO
Zybisys —Tiruchchirappalli, Tamil Nadu
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SENIOR BUSINESS ANALYST
Akra Tech —Chennai, Tamil Nadu
- Part-time
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Sr Python Developer
WE Excel Software —Chandigarh
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Akra Tech —Chennai, Tamil Nadu
- Part-time
- Social media management
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Engineering Manager
iSOCRATES —Bengaluru, Karnataka
- Computer Science
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- Master's degree
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Solution Architect
Simform —Ahmedabad, Gujarat
- Full-time
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Senior Software Engineer - Java
Zycus —Mumbai, Maharashtra
- Full-time
- Java
- Project management
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Senior Technical Architect
Hype Digitals & Promotions —Mohali, Punjab
- From ₹1,00,000 a month
- Full-time
- Azure
- Computer Science
- Java
Quick apply
3d

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AI Automation Engineer

HRhelpdesk
Indore, Madhya Pradesh

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Job details

Full-time

Benefits

Paid holidays
Health insurance

Qualifications

Node.js
Law
MCP
React
Full-stack development
NoSQL
English
MongoDB
Master's degree
REST
APIs
GraphQL
AI
TypeScript
Python
SDLC

Full job description

Job Information

Job Opening ID

ZR_782_JOB

Date Opened

05/29/2026

Industry

IT Services

Work Experience

5-10 years

Job Type

Full time

Salary

Confidential

City

Indore

State/Province

Madhya Pradesh

Country

India

Zip/Postal Code

452001

Job Description

The Company, a USA Subsidiary is a rapidly growing, private equity-backed SaaS company founded by engineers, focused on building scalable, high-quality products. Our solutions support over 3000 organizations, enabling them to manage grants, scholarships and philanthropic initiatives effectively. We offer cloud-based platforms that power the end-to-end lifecycle of grants, scholarships, fellowships, employee giving, and volunteer programs. In our organization, we foster a collaborative, innovation-driven culture with a flexible work environment and competitive benefits.

About the role

We're building the AI layer that makes our grant management platform - and the people who build it -more leveraged. We've already shipped the foundations: an internal MCP server with a growing tool catalog, a shared context layer that grounds agents in real product data, and a QA AIification initiative that's moving testing from local dev into staged release. We need an engineer to push this work forward

end-to-end.

You'll design, build, and operate agentic systems and AI-powered automations that touch real production workflows - both internal (engineering, QA, support tooling) and customer-facing (workflow rules, document processing, intelligent assistance inside the product). This is a hands-on builder role for someone who's excited about LLMs as a serious engineering substrate, not a demo.

Responsibilities:

Design, build, and maintain MCP servers and tools that expose our internal systems (MongoDB, GraphQL APIs, internal services) to LLM agents safely and usefully

Own AI-powered automations across the SDLC: spec-to-code workflows, automated PR review, QA generation, release-time checks

- Build customer-facing AI features - for example, replacing complex DSL-based rule engines with plain-English LLM-driven workflow creation

Develop the shared context layer: retrieval, grounding, prompt assembly, and the evaluation harness that keeps it honest

- Implement evals, regression tests, and observability for LLM systems - latency, cost, accuracy, hallucination rate, drift

Partner with product engineering teams to integrate AI capabilities into the Node.js / React/GraphQL / MongoDB / Apollo Federation stack

Set patterns and guardrails: prompt management, tool security, rate limits, dry-run/safety modes for destructive operations

- Stay close to the frontier - evaluate new models, frameworks, and patterns as they emerge and bring the useful ones in

How we will take care of you:

Motivating compensation

Medical & Life insurance

Paid Holidays

Great working environment

Rapid career development opportunities

Requirements

Must Haves:

4+ years of backend or full-stack engineering experience, with at least 1 year focused on LLM applications, agents, or AI-powered automation in production

Strong proficiency with Python and/or TypeScript/Node.js

Hands-on experience with the LLM application stack: OpenAI/Anthropic APIs, function calling/tool use, structured outputs, streaming

Familiarity with MCP (Model Context Protocol) or comparable agent-tooling protocols and frameworks (LangGraph, LlamaIndex, custom orchestration)

- Practical experience with retrieval (vector or hybrid), prompt engineering, and LLM evaluation -you know how to make these systems reliable, not just functional- Solid software engineering fundamentals: testing, observability, code review, incident response

Comfort with MongoDB or similar NoSQL databases, and with REST/GraphQL APIs

Nice to haves:

Experience operating Claude Code, Cursor, or similar agentic coding tools at team or org scale

Background in QA automation, test generation, or developer productivity tooling

Familiarity with Apollo Federation, GraphQL subgraph architecture

Experience with workflow/rules engines, DSLs, or no-code platforms

Track record of shipping AI features that customers (not just internal users) actually adopt

Familiarity with Playwright, Bruno, mabl, k6, or similar testing tools

How you'll be measured:

- AI capabilities shipped to internal teams and customers - adoption, reliability, retention of use

Engineering velocity unlocked across the org through automation

Operational health of AI systems: cost per outcome, accuracy/eval scores, incident rate

Quality of the patterns and primitives you establish for others to build on

Benefits

How we will take care of you:

Motivating compensation

Medical & Life insurance

Paid Holidays

Great working environment

Rapid career development opportunities

Apply Now

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