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Full Stack Engineer (Mid–Senior) – Enterprise AI Platforms
Full Stack Engineer (Mid–Senior) – Enterprise AI Platforms

Full Stack Engineer (Mid–Senior) – Enterprise AI Platforms at Ampera Technologies · Bengaluru (Bangalore), Chennai · 4 - 7 years · Profitable · Posted 23 Apr 2026

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Full Stack Engineer (Mid–Senior) – Enterprise AI Platforms

Faisal AshrafNomani's profile picture
Posted by Faisal AshrafNomani
4 - 7 yrs
Best in industry
Bengaluru (Bangalore), Chennai
Skills
skill iconReact.js


About Ampera

Ampera builds enterprise-grade AI platforms that sit at the intersection of large-scale data systems, intelligent orchestration, and applied AI.

Our products help Fortune 1000 companies optimize operations, manage risk, and unlock decision intelligence using AI, LLMs, and agentic workflows.





Role Overview

We are looking for a strong Full Stack Engineer who has built production-grade enterprise applications, worked with large datasets, and is excited about integrating AI systems and LLM-powered workflows into real-world platforms.

This is not a UI-only or API-only role.

You’ll own end-to-end system design, from frontend experiences to backend orchestration and AI integration.

 

What You’ll Work On

  • Enterprise web platforms used by analysts, admins, and leadership
  • High-scale data-intensive applications (query orchestration, risk intelligence, estimation engines)
  • AI-augmented workflows (LLMs, agents, optimizers, explainability layers)
  • Secure, governed, multi-tenant systems with role-based access

Key Responsibilities

Full Stack Development

  • Design and build scalable web applications (frontend + backend)
  • Develop API-first backend services for enterprise workflows
  • Build admin dashboards, analyst workflows, and decision-ready UIs
  • Ensure performance, reliability, and maintainability at scale

Backend & Data Systems

  • Work with large-scale relational databases (Azure Synapse, Redshift, Snowflake, PostgreSQL, SQL Server, etc.)
  • Design data models for high-volume, analytical workloads
  • Implement caching, orchestration, background processing, and async workflows
  • Integrate with enterprise systems (identity, BI tools, data platforms)

AI / LLM Integration

  • Integrate LLMs (OpenAI, Azure OpenAI, etc.) into production systems
  • Build AI-powered services:
  • Query optimization
  • Risk scoring & explainability
  • Estimation & prediction workflows
  • Implement agentic AI patterns (multi-step reasoning, tool-using agents, orchestration)
  • Work closely with ML engineers to productionize AI models

Enterprise Readiness

  • Implement RBAC, audit logging, governance, and guardrails
  • Design systems with security, compliance, and observability in mind
  • Contribute to CI/CD pipelines, deployments, and production monitoring

Required Skills & Experience

Core Engineering

  • 4–8+ years of experience as a Full Stack Engineer
  • Strong backend experience with Python (FastAPI preferred) or equivalent
  • Solid frontend experience with React / modern JS frameworks
  • Strong understanding of REST APIs, async processing, microservices

Data & Systems

  • Hands-on experience with large databases and complex schemas
  • Strong SQL skills and experience optimizing queries
  • Experience building enterprise-grade, data-heavy applications

AI / Modern Stack

  • Practical experience integrating LLMs or AI services into applications
  • Familiarity with:
  • Prompting & structured outputs
  • AI evaluation & guardrails
  • Explainability and risk-aware AI
  • Exposure to agentic AI frameworks or multi-step AI workflows is a big plus

Nice-to-Have (Strong Differentiators)

  • Experience building AI-powered SaaS or internal enterprise platforms
  • Background in analytics, risk systems, finance, supply chain, or operations
  • Experience with Redis, message queues, background workers
  • Familiarity with Azure / AWS, containerization, Kubernetes
  • Ability to translate business problems → system design

What We Look For (Beyond Skills)

  • Strong systems thinking — you see the whole picture
  • Comfortable operating in ambiguous, zero-to-one builds
  • Ability to reason about scale, cost, and enterprise constraints
  • Builder mindset — you ship, iterate, and own outcomes

Why Join Ampera

  • Work on real enterprise AI platforms, not demos or chatbots
  • Exposure to LLMs, agentic AI, and applied AI at scale
  • High ownership, senior-heavy team, minimal bureaucracy
  • Opportunity to shape core architecture and AI strategy

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About Ampera Technologies

Founded :
2024
Type :
Services
Size :
20-100
Stage :
Profitable

About

At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions

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Interview Focus Areas

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Key Responsibilities

  • Design, develop and maintain scalable full-stack applications using Python, React.js, MongoDB and Java/Spring Boot.
  • Build production-grade Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
  • Develop RAG pipelines, AI agents, tool calling, memory management, planning and agent orchestration.
  • Work with LangChain, LangGraph, MCP, vector databases and semantic search.
  • Develop Python-based APIs, microservices and asynchronous applications using FastAPI/Flask/Django.
  • Build REST APIs and event-driven microservices with focus on scalability, performance and resilience.
  • Integrate LLMs, embeddings, vector stores and external enterprise tools/services.
  • Implement prompt engineering, LLM evaluation, guardrails and AI observability.
  • Develop responsive front-end applications using React.js.
  • Work with MongoDB, SQL and hybrid data models.
  • Implement CI/CD pipelines and support cloud/OCP deployments.
  • Follow secure coding, testing, code quality and performance best practices.
  • Participate in architecture, technical design, code reviews and mentoring of team members.
  • Collaborate with business and technical stakeholders to translate requirements into scalable solutions.

Mandatory Skills

  1. Python
  2. React.js
  3. Gen AI / Agentic AI
  4. RAG + LLM
  5. LangChain / LangGraph
  6. MongoDB
  7. Java + Spring Boot
  8. REST APIs / Microservices
  9. Vector Databases / Embeddings
  10. MCP / AI Agent orchestration

Good to Have

  • FastAPI / Flask / Django
  • Kafka / Solace
  • Docker / Kubernetes
  • AWS / Azure / GCP / OCP
  • CI/CD – Jenkins / GitHub Actions
  • LLMOps / AI evaluation / observability
  • ELK / Grafana / Splunk / AppDynamics
  • SQL / NoSQL
  • Agile/Scrum
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Shubham Vishwakarma's profile image

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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