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Fullstack_AI Engineer
Fullstack_AI Engineer

Fullstack_AI Engineer at Appiness Interactive · Pune · 4 - 7 years · ₹20L - ₹22L / yr · Posted 14 Jul 2026

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Fullstack_AI Engineer

Archana M's profile picture
Posted by Archana M
4 - 7 yrs
₹20L - ₹22L / yr
Pune
Skills
skill iconPython
skill iconReact.js
Multi-agent Systems

We're Hiring | Full Stack AI Engineer – Multi-Agent Systems

We are looking for a Full Stack AI Engineer who can own end-to-end feature delivery – from designing agent communication patterns and orchestration logic on the backend, to building intuitive interfaces for configuring, monitoring, and debugging agent workflows. You will work directly with the architect and product owner to translate orchestration concepts (agent-to-agent messaging, tool use, handoffs, memory) into a production-grade system.

This is a hands-on builder role. You will not be writing strategy decks – you will be shipping agents, APIs, and UI.


Location: Pune

Experience: 4–7 Years (1.5+ years in GenAI/AI Agents)

Employment Type: Full-time


Key Responsibilities


Backend & Agent Development


•       Design and implement multi-agent workflows using AG2 (AutoGen) and/or LangGraph – including agent roles, conversation patterns, handoffs, and termination conditions.

•       Build and maintain FastAPI services that expose orchestration capabilities (agent registration, task submission, run status, streaming responses) to the frontend and external consumers.

•       Implement tool/function calling, structured outputs, and memory layers (short-term, long-term, vector-based) for agents.

•       Integrate LLM providers (OpenAI, Anthropic, AWS Bedrock, or local models via Ollama) with proper retry, timeout, and cost controls.

•       Write clean, testable Python with type hints, pydantic models, and clear separation between orchestration logic and infrastructure.


Frontend Development


•       Build React-based interfaces for configuring agents, visualising agent conversations, inspecting tool calls, and debugging runs.

•       Implement streaming UI (SSE/WebSockets) to render token-by-token agent responses and intermediate steps.

•       Collaborate on UX for workflow builders, run history, and observability dashboards.

System & Production Concerns

•       Containerise services with Docker and contribute to CI/CD pipelines.

•       Add logging, tracing, and basic evaluation hooks for agent runs (latency, token usage, success rates).

•       Participate in code reviews, design discussions, and incremental hardening of the platform.


Must-Have Skills


•       Full stack experience (5+ years): strong Python (FastAPI or similar) on the backend AND React on the frontend. Comfortable owning a feature across both layers.

•       Hands-on with at least one agent framework: AG2 (AutoGen), LangGraph, LangChain Agents, or CrewAI. Must have actually built and run multi-agent flows, not just read about them.

•       LLM application development: prompt design, tool/function calling, structured outputs, handling streaming responses, and basic context management.

•       RAG fundamentals: chunking strategies, embeddings, vector stores (pgvector / Qdrant / Weaviate / FAISS), and retrieval evaluation. Bonus for hybrid (sparse + dense) retrieval.

•       Database skills: PostgreSQL – schema design, indexing, and writing reasonable queries.

•       API & async patterns: REST design, async Python (asyncio), background jobs, and streaming endpoints.

•       Version control & collaboration: Git, PR-based workflows, writing clear commit messages and design notes.


Good-to-Have Skills


•       Experience with GCS for deploying AI workloads.

•       Familiarity with LLMOps – tracing (LangSmith / Langfuse / OpenTelemetry), evaluation frameworks, and prompt versioning.

•       Exposure to MCP (Model Context Protocol) or A2A (agent-to-agent) communication standards.

•       Experience running local LLMs (Ollama, vLLM) for prototyping or cost-sensitive workloads.

•       Knowledge of WebSockets / SSE for real-time UIs.

•       Basic understanding of fine-tuning concepts (LoRA / QLoRA) – we are not expecting trainers, just awareness.

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Experience with relational/NoSQL databases, caching and cloud infrastructure.

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Application Link:https://beyond.ciltriq.com/apply/BUILD


Description:

Join a team building AI-powered systems that solve complex business problems and automate operational workflows across document processing, voice agents, enterprise integrations, workflow automation, and multi-agent systems.


Strong full-stack foundations: frontend state management, asynchronous user experiences and performance; backend API design, authentication, data modelling, databases, queues and distributed systems.


Strong coding ability in Python and JavaScript or TypeScript, with practical experience in modern frontend frameworks and backend services.


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We are looking for a skilled Python Full Stack / Agentic AI Engineer to design, develop, and deploy AI-powered applications and intelligent agentic workflows. The ideal candidate should have strong expertise in Python, FastAPI, LLMs, RAG, LangChain/LangGraph, and modern full-stack development.

You will work on building scalable backend services, integrating Large Language Models, developing AI agents, implementing Retrieval-Augmented Generation (RAG) pipelines, and creating production-ready AI applications.

Key Responsibilities

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  • Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source models.
  • Develop prompt engineering strategies and structured LLM workflows.
  • Work with vector databases and embedding models for semantic search and knowledge retrieval.
  • Build APIs and microservices for AI-powered applications.
  • Integrate AI services with databases, third-party APIs, and enterprise systems.
  • Develop conversation memory, tool calling, function calling, and agent orchestration capabilities.
  • Implement evaluation, monitoring, logging, guardrails, and error handling for AI applications.
  • Optimize applications for performance, scalability, reliability, and cost.
  • Collaborate with product managers, frontend developers, data engineers, and other stakeholders.
  • Write clean, maintainable, well-tested, and production-ready code.
  • Participate in architecture discussions, code reviews, testing, and deployment activities.

Required Skills

Programming & Backend

  • Strong proficiency in Python.
  • Hands-on experience with FastAPI, REST APIs, and backend development.
  • Strong understanding of asynchronous programming, API design, authentication, and middleware.
  • Experience with SQL/NoSQL databases.

Generative AI / Agentic AI

  • Strong understanding of LLMs and Generative AI.
  • Hands-on experience building AI Agents / Agentic AI applications.
  • Experience with LangChain and/or LangGraph.
  • Knowledge of agent orchestration, tool calling, function calling, memory, and workflow management.
  • Strong understanding of prompt engineering.

RAG

  • Experience designing and implementing RAG architectures.
  • Knowledge of document ingestion, chunking, embeddings, vector search, retrieval, reranking, and response generation.
  • Experience with vector databases such as FAISS, Chroma, Pinecone, Weaviate, Qdrant, or similar.

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  • Experience integrating commercial or open-source LLMs.
  • Understanding of embeddings, context windows, temperature, token usage, and model selection.
  • Experience with structured outputs and LLM-based workflows.
  • Familiarity with LLM evaluation and observability is a plus.

Full Stack

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  • Experience with React.js or similar frontend frameworks is preferred.
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Key Responsibilities

  • Design, develop, and maintain scalable Python backend applications for enterprise use cases.
  • Develop robust REST APIs and microservices using Python frameworks such as FastAPI, Flask, or Django.
  • Design and implement scalable backend services with proper API integration, authentication, error handling, logging, and monitoring.
  • Develop responsive and scalable React.js frontend applications.
  • Implement React Hooks, state management, API integration, reusable components, and frontend development.
  • Integrate React.js applications with Python backend APIs and microservices.
  • Design and develop Generative AI and LLM-powered applications.
  • Build and integrate Agentic AI / AI Agent solutions for enterprise use cases.
  • Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise data and knowledge sources.
  • Work with embeddings, vector databases, and vector search for semantic retrieval and knowledge-based applications.
  • Develop AI agent workflows using frameworks such as LangChain, LangGraph, Google ADK, or Semantic Kernel.
  • Implement tool calling and function calling to enable AI agents to interact with APIs, databases, enterprise systems, and external services.
  • Apply prompt engineering techniques to improve LLM response quality, accuracy, consistency, and reliability.
  • Integrate LLMs and GenAI capabilities into full-stack applications.
  • Develop multi-step AI workflows, agent orchestration, and intelligent automation solutions.
  • Design APIs and services for seamless integration between AI components, backend services, databases, and frontend applications.
  • Work with cloud platforms such as AWS, Azure, or GCP for application and AI solution deployment.
  • Develop production-ready applications with focus on scalability, performance, security, reliability, and maintainability.
  • Troubleshoot and optimize backend, frontend, API, RAG, LLM, and Agentic AI components.
  • Collaborate with architects, software engineers, AI/ML engineers, product teams, and business stakeholders.
  • Participate in code reviews, technical discussions, testing, deployment, and production support.

Mandatory Skills

  • Python Backend Development
  • REST API / Microservices
  • FastAPI / Flask / Django
  • React.js
  • React Hooks / State Management
  • Frontend Development & API Integration
  • GenAI / LLM
  • Agentic AI
  • RAG
  • Embeddings / Vector Search
  • LangChain / LangGraph / Google ADK / Semantic Kernel
  • Prompt Engineering
  • Tool Calling / Function Calling
  • Cloud – AWS / Azure / GCP

Preferred Candidate Profile

  • 8.5+ years of overall software development experience.
  • Strong hands-on experience in Python backend development and API/microservices development.
  • Strong experience in React.js and full-stack application development.
  • Practical experience building GenAI/LLM applications.
  • Hands-on experience with Agentic AI and AI agent frameworks.
  • Good understanding of RAG, embeddings, vector search, and LLM-based application architecture.
  • Experience with LangChain, LangGraph, Google ADK, Semantic Kernel, or equivalent agent frameworks.
  • Strong understanding of prompt engineering and tool/function calling.
  • Experience integrating AI capabilities with APIs, databases, enterprise applications, and external systems.
  • Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
  • Strong problem-solving, debugging, communication, and collaboration skills.
  • Candidates should be available for immediate / short-term joining.


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Remote only
3 - 15 yrs
₹6L - ₹12L / yr (ESOP available)
skill iconPython
skill iconC#
skill iconReact.js

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

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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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