Solutions Architect

Geta AI Labs Private Limited; Pune District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A cutting-edge AI product company based in Pune is seeking a skilled professional to design and implement innovative software solutions. You will work with modern programming languages and tools, focusing on architecture, DevOps, and AI integration. Ideal candidates should possess strong technical and soft skills, and be passionate about building products that deliver real business value. Join us in creating AI-driven products that make an impact.

Qualifications

• Strong skills in modern programming languages such as TypeScript, Java, Go, or Python.
• Experience with DevOps/MLOps practices and tools.
• Knowledge of Infrastructure as Code tools like Terraform.

Responsibilities

• Design modular, event-driven, or microservice architectures.
• Implement monitoring for logs, traces, and metrics.
• Optimize APIs and integrations with third-party services.

Skills

Programming

TypeScript / Java / Go/Python

DevOps / MLOps

CI/CD

Infrastructure as Code (Terraform / CDK)

Monitoring (logs, traces, metrics)

APIs & integrations

Relational DBs + NoSQL

AI & ML Integration

Soft Skills

Tools

Terraform

CI/CD tools

Vector databases (Pinecone, Weaviate, FAISS)

Job description

Geta.ai builds cutting-edge AI-driven products that help businesses scale smarter and faster. We thrive on solving complex problems with simple, elegant solutions and are looking for leaders who can drive growth and partnerships as we scale.

Role Overview

Job Description

• Programming
• One of: TypeScript / Java / Go/Python
• DevOps / MLOps
• CI/CD
• Infrastructure as Code (Terraform / CDK)
• Monitoring (logs, traces, metrics)
• Identity & access
• AuthN/AuthZ (OAuth2, OIDC, JWT), SSO
• Role-based access control (RBAC)
• Designing modular, event-driven, or microservice architectures
• Handling growth, latency, and cost trade-offs
• Serverless vs containerized workloads
• Multitenancy architecture
• APIs & integrations
• REST / GraphQL
• Third-party integrations (LLMs, data providers, internal services)
• Storage
• Relational DBs + NoSQL
• Data lakes/warehouses
• Data governance
• Access control
• Auditability (especially for enterprise customers)

Nice to have

• AI & ML Integration (Not Pure Data Science)
• You’re usually not expected to build models from scratch, but you must know:
• LLM integration
• Function calling / tool use
• RAG (Retrieval Augmented Generation)
• Vector databases (Pinecone, Weaviate, FAISS)
• Embeddings, chunking strategies
• Inference architecture
• Latency vs accuracy trade-offs
• Caching strategies (prompt & response caching)
• Monitoring hallucinations, drift, and cost usage

2. Product & Business Thinking (Often Overlooked)

• Startup architects must think beyond tech:
• Build good enough, iterate fast
• Buy vs build decisions
• When to use APIs vs custom solutions
• User experience with AI
• Guardrails
• Explainability
• AI features tied to business value, not hype

3. Soft Skills (Extremely Important in Startups)

• More important than in large enterprises:
• Communicating trade-offs to founders & investors
• Mentoring engineers
• Working with ambiguity and incomplete requirements