Architect – Agentic AI Engineering

Algoleap Technologies; Hyderabad; On-site; INR 400,000 - 600,000; Full time

Job summary

Algoleap Technologies Pvt Ltd is seeking an experienced Architect to lead the design, hardening, and scaling of agentic AI systems, transforming prototype LLM apps into production-grade platforms. This role blends AI engineering with software architecture and requires hands-on backend depth.

You will design agentic workflows, own prompt engineering, and integrate LLM capabilities into scalable architectures, with deployment on AWS and/or Azure and a focus on security and cost efficiency.

Qualifications

• Agentic AI frameworks experience
• Prompt engineering and refinement for production use cases
• Proficiency in Python, FastAPI, async/await, performance tuning
• Strong software architecture and system design background
• Hands-on experience deploying on AWS/Azure with scalable backend services
• Ability to scale prototypes to production-grade systems
• Excellent communication of architectural decisions

Responsibilities

• Architect and build agentic AI workflows with LangGraph and Claude Code
• Own prompt engineering strategy for reliability and cost efficiency
• Integrate LLM capabilities into robust production architectures
• Refactor prototypes into production-grade systems with engineering rigor
• Develop backend services in Python (FastAPI) and optimize performance
• Design scalable, secure, and well-documented APIs

Skills

Agentic AI Frameworks

Prompt Engineering

Python Engineering

Software Architecture

AWS/Azure experience

Async programming

LLM integration

Tools

LangGraph

Claude Code

FastAPI

Cloud deployment

Async patterns

Job description

Algoleap Technologies Pvt Ltd | Full time

Job Description: Architect – Agentic AI Engineering

Role: Architect

Engagement Type: Contract-to-Hire (C2H)

About the Role

We are looking for an experienced Architect to lead the design, hardening, and scaling of agentic AI systems — taking prototype-stage LLM applications and evolving them into production‑grade, enterprise‑ready platforms. This role sits at the intersection of AI engineering and software architecture, requiring hands‑on depth in agentic frameworks alongside strong fundamentals in backend systems design and cloud deployment.

Key Responsibilities

Agentic AI Development

• Design and build agentic workflows using frameworks such as LangGraph, and tools like Claude Code, to orchestrate multi‑step, tool‑using AI agents
• Own prompt engineering strategy — designing, testing, and iterating on prompts for reliability, consistency, and cost efficiency
• Evaluate and integrate LLM capabilities into broader application architectures

Prototype‑to‑Production Engineering

• Take early‑stage AI prototypes and refactor them into robust, maintainable, production‑grade systems
• Identify and remediate technical debt, brittle logic, and scalability bottlenecks common in fast‑built AI proofs‑of‑concept
• Establish engineering rigor (testing, observability, error handling, versioning) around previously ad hoc AI systems
• Architect and develop backend services in Python, using FastAPI and async programming patterns
• Optimize application performance, latency, and throughput for AI‑driven workloads
• Design clean, well‑documented APIs that support both internal and external consumption

Software Architecture & Design

• Apply sound software architecture principles and design patterns to ensure systems are modular, scalable, and maintainable
• Make and document key architectural decisions (system design, data flow, integration patterns, trade‑offs)
• Set technical standards and provide architectural guidance to engineering teams
• Design and deploy solutions on AWS and/or Azure, leveraging cloud‑native services for compute, storage, and orchestration
• Ensure systems are built with security, cost‑efficiency, and scalability in mind from a cloud architecture standpoint

Required Skills & Experience

Area

Agentic AI Frameworks

Hands‑on experience with LangGraph, Claude Code, or comparable agent orchestration tools

Prompt Engineering

Demonstrated experience designing and refining LLM prompts for production use cases

Python Engineering

Strong proficiency in Python, FastAPI, async/await patterns, and performance optimization

Software Architecture

Solid grounding in design patterns, system design, and architecture for production systems

Working experience with AWS and/or Azure (compute, storage, deployment pipelines)

Systems Thinking

Proven ability to take a prototype and scale it into a reliable, production‑ready system

Ideal Candidate Profile

• 8+ years of overall software engineering experience, with a meaningful portion in AI/LLM‑based systems
• Comfortable operating as an individual architect/senior IC — able to both write code and make architectural calls
• Experience working in fast‑moving, ambiguous environments where systems evolve from PoC to production under time pressure
• Strong communication skills to justify architectural decisions to both technical and non‑technical stakeholders