Bounteous - Full Stack Developer - Generative AI

Accolite

Hyderabad

On-site

INR 2,800,000 - 4,400,000

Full time

26 hours ago
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Job summary

Accolite is seeking a talented AI Generative Full Stack Developer to design, build, and deploy AI-powered applications using Python and React. You will work on integrating LLM capabilities into production-ready features, creating robust backends and responsive frontends.

You will design agentic systems, implement prompt engineering workflows, and optimize performance with modern tools. Join a fast-paced team driving cutting-edge AI solutions for real-world impact.

Qualifications

  • Hands-on experience with LLM APIs (OpenAI, Anthropic, Cohere, or similar).
  • Experience building agentic systems (tool use, memory, multi-step reasoning).
  • Familiarity with prompt engineering techniques (chain-of-thought, few-shot, RAG).
  • Understanding of fine-tuning and model evaluation concepts.
  • Strong async Python (or TypeScript) and REST/GraphQL API development.

Responsibilities

  • Design and develop AI-powered full stack applications using Python (backend) and React (frontend).
  • Build and maintain agentic frameworks and LLM pipelines.
  • Integrate generative AI APIs into scalable web applications.
  • Develop RESTful and GraphQL APIs to connect AI backends with React frontends.
  • Implement RAG systems using vector databases.
  • Build and optimize prompt engineering workflows and evaluation pipelines.
  • Collaborate with product, design, and data science teams to ship AI features end-to-end.
  • Write clean, testable, and well-documented code.
  • Monitor, debug, and optimize AI model performance in production.

Skills

Python
React.js
TypeScript
FastAPI
Django/Flask
Async programming
SQL
NoSQL
Docker
AWS/GCP/Azure
LangChain
LlamaIndex
OpenAI API
Anthropic SDK

Tools

LangChain
LlamaIndex
OpenAI API
Anthropic SDK
LangSmith
Weaviate/ChromaDB
LLM pipelines
CI/CD

Job description

We are looking for a talented and passionate AI Generative Full Stack Developer to join our growing engineering team. You will be responsible for designing, building, and deploying intelligent AI-powered applications combining cutting-edge generative AI capabilities with robust full stack development using Python and React. You will work at the intersection of AI research and product engineering, turning LLM capabilities into real-world, production-ready features.

We are looking for a talented and passionate AI Generative Full Stack Developer to join our growing engineering team. You will be responsible for designing, building, and deploying intelligent AI-powered applications combining cutting-edge generative AI capabilities with robust full stack development using Python and React. You will work at the intersection of AI research and product engineering, turning LLM capabilities into real-world, production-ready features.

Key Responsibilities
  • Design and develop AI-powered full stack applications using Python (backend) and React (frontend).
  • Build and maintain agentic frameworks and LLM pipelines using tools like LangChain, LlamaIndex, or custom implementations.
  • Integrate generative AI APIs (OpenAI, Anthropic Claude, Gemini, etc.) into scalable web applications.
  • Develop RESTful and GraphQL APIs to connect AI backends with React frontends.
  • Implement RAG (Retrieval-Augmented Generation) systems using vector databases (Pinecone, Weaviate, ChromaDB).
  • Build and optimize prompt engineering workflows and evaluation pipelines.
  • Collaborate with product, design, and data science teams to ship AI features end-to-end.
  • Write clean, testable, and well-documented code.
  • Monitor, debug, and optimize AI model performance in production.
  • Stay current with the rapidly evolving generative AI landscape.
Required Skills & Experience
  • Claude API & Anthropic SDK proficiency Hands-on experience with the Messages API, tool use / function calling, system prompt design, and model selection trade-offs (Sonnet vs. Opus vs. Haiku). Familiarity with context window management and token budgeting.
  • Agentic loop architecture Ability to design reliable multi-step agent loops: tool orchestration, retry logic, error recovery, and knowing when to stop or elevate rather than loop indefinitely.
  • Tool/MCP integration Experience building and connecting tools (internal APIs, databases, external services) via Anthropic's tool use schema or MCP servers, including input validation and graceful failure handling.
  • Prompt engineering & evaluation Skilled at structured prompting (system prompts, few-shot examples, XML tagging), and building prompt eval harnesses to measure output quality, regression-test changes, and tune instructions systematically.
  • Observability & auditability Knows how to log full agent traces (inputs, tool calls, intermediate outputs, final responses) in a structured, queryable format. Experience with tools like LangSmith, Braintrust, Helicone, or custom tracing pipelines.
  • Measurement & KPI design Can define and instrument meaningful agent metrics: task completion rate, tool call accuracy, hallucination rate, latency per step, cost per run, and human-in-the-loop escalation rate. Connects agent telemetry to business outcomes.
  • Human-in-the-loop & guardrails Understands when to inject human review checkpoints, how to design approval gates for high-stakes actions, and how to implement input/output guardrails (content filtering, schema validation, confidence thresholds).
  • Cost & latency optimization - Experience profiling and reducing inference costs through prompt caching, batching, streaming, and appropriate model tiering without sacrificing reliability.
  • Security & data handling - Awareness of prompt injection risks, credential/secret hygiene in agentic contexts, PII handling, and least-privilege design when agents have access to real systems or external APIs.
  • Software engineering fundamentals Strong async Python (or TypeScript), testing discipline (unit + integration tests for agent components), CI/CD, and the ability to decompose complex agent systems into maintainable, modular code.
Ai/Llm
  • Hands-on experience with LLM APIs (OpenAI, Anthropic, Cohere, or similar).
  • Experience building agentic systems (tool use, memory, multi-step reasoning).
  • Familiarity with prompt engineering techniques (chain-of-thought, few-shot, RAG).
  • Understanding of fine-tuning and model evaluation concepts.
Backend (Python)
  • Strong proficiency in Python 3.x.
  • Experience with FastAPI or Django / Flask.
  • Working knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB, Redis).
  • Familiarity with async programming and background task queues (Celery, RQ).
  • Experience with Docker and deploying to cloud platforms (AWS, GCP, or Azure).
Frontend (React)
  • Strong proficiency in React.js and modern JavaScript (ES6+).
  • Experience with TypeScript.
  • Familiarity with state management (Redux, Zustand, or Context API).
  • Ability to build streaming UI for LLM outputs (token-by-token rendering).
  • Basic understanding of UX principles for AI interfaces.
General
  • Experience with Git and collaborative development workflows.
  • Comfort working in fast-paced, ambiguous environments.
  • Strong problem-solving and communication skills.
Nice To Have
  • Certified Claude Architect Foundations (CCA-F).
  • Experience with Claude Code, Cursor, or other AI-assisted development tools.
  • Contributions to open-source AI projects.
  • Experience with multi-agent frameworks (AutoGen, CrewAI, LangGraph).
  • Knowledge of MLOps practices and model deployment (MLflow, Weights & Biases).
  • Familiarity with WebSockets for real-time AI streaming.
  • Experience with Kubernetes or serverless architectures.

(ref:hirist.tech)

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