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: Architect – Agentic AI Engineering

Role: Architect

Engagement Type: Contract-to-Hire (C2H)

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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.

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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

Backend Engineering

- 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

Cloud & Infrastructure

- 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

[hr align="center" size="1" width="100%"] Required Skills & Experience

Area

Expectation

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

Cloud Platforms

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

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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 rapid-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

📌 Architect – Agentic AI Engineering (Bengaluru)
🏢 Algoleap Technologies
📍 Bengaluru