AI Solutions Architect

Key Responsibilities

Client

Engagement & Solution Design

• Engage directly with clients to understand

business problems, operational bottlenecks, and automation opportunities

• Translate business requirements into detailed AI

architecture blueprints - covering model selection, infrastructure, data flow,

and integration points

• Recommend cloud vs. on-premise vs. hybrid AI

deployment based on client security posture, data sensitivity, and budget

• Present AI solution proposals to both technical

and non-technical stakeholders with clarity

AI

Implementation & Development

• Design and deploy AI automation workflows using

n8n, Make, and Zapier integrated with LLM capabilities

• Integrate OpenAI, Anthropic Claude, Google

Gemini, and other LLM APIs into client systems and internal products

• Set up and configure local AI deployments using

Ollama, LM Studio, or similar frameworks on client infrastructure

• Build and maintain RAG (Retrieval-Augmented

Generation) pipelines with vector databases (Pinecone, Weaviate, Qdrant,

ChromaDB)

• Develop AI Agents and AI Assistants tailored to

specific business use cases - customer support, sales enablement, operations,

inventory

• Build and deploy AI chatbots integrated into

websites, WhatsApp, Shopify storefronts, and internal tools

• Configure and manage MCP (Model Context

Protocol) servers for context-aware AI deployments

E-Commerce

& Platform AI

• Implement AI-powered features within Shopify

ecosystems - smart recommendations, AI search, automated customer interactions

• Integrate AI workflows into Zoho Flow, Zoho CRM,

and other business platforms used by SME and enterprise clients

• Build AI-assisted ERP/SAP integration layers for

data transformation and decision support

Infrastructure

& Security

• Set up GPU/AI server infrastructure

(NVIDIA-based or cloud GPU instances) for local model deployment

• Containerize AI services using Docker; manage

deployment in basic server environments

• Enforce AI security best practices - data

privacy, prompt injection defense, model access control, audit logging

• Evaluate and implement on-premise AI deployments

for clients with data residency or compliance requirements

Continuous

Improvement

• Stay current on fast-moving AI tooling, models,

and frameworks - bring new ideas into the practice proactively

• Document architectures, deployment playbooks,

and integration guides for internal knowledge sharing

• Mentor junior team members on AI implementation

practices

Required Technical

Skills

• LLM Integration: Hands-on experience integrating

OpenAI GPT, Anthropic Claude, or Google Gemini APIs into production systems

• Local AI Deployment: Practical experience with

Ollama, LM Studio, or equivalent for running open-weight models locally

• RAG & Vector Databases: Ability to build

end-to-end RAG pipelines; working knowledge of at least one vector DB

• AI Agents & Assistants: Built at least one

functional AI agent or assistant - tool-using, multi-step, or autonomous

• Automation Platforms: Hands-on experience with

n8n, Make (Integromat), or Zapier for workflow automation

• API Integrations: Comfortable working with REST

APIs, webhooks, and third-party integration patterns

• Prompt Engineering: Practical understanding of

system prompts, few-shot prompting, chain-of-thought, and output structuring

• Programming: Working knowledge of Python or

Node.js - enough to build integrations, scripts, and lightweight services

• Docker & Deployment: Ability to containerize

AI services and deploy to Linux-based server environments

• AI Security Basics: Awareness of data privacy in

AI systems, prompt injection risks, and secure API key management

Requirements

Preferred Skills

• Experience with MCP (Model Context Protocol)

server setup and configuration

• Shopify app development or AI integrations

within the Shopify ecosystem

• Zoho Flow / Zoho One automation experience
• Familiarity with ERP/SAP data structures and

integration patterns

• Knowledge of GPU infrastructure - NVIDIA CUDA,

cloud GPU provisioning (AWS, GCP, Azure)

• Experience with LangChain, LlamaIndex, or

similar orchestration frameworks

• Working knowledge of embedding models and

semantic search

• WhatsApp Business API integrations
• Basic understanding of fine-tuning or model

customization workflows

• Exposure to enterprise AI governance and

compliance frameworks

Experience

Requirements

• 3 to 5 years of total professional experience in

technology roles

• Minimum 1.5 to 2 years of direct, hands-on AI/ML

implementation experience (not just exposure)

• At least 2 to 3 end-to-end AI projects delivered

- from problem definition to deployment

• Prior experience in a digital agency, product

company, or consulting environment is strongly preferred

• Client-facing experience or technical pre-sales

exposure is a significant plus

• Experience in e-commerce, retail, or B2B SaaS

verticals preferred

Note: We value demonstrated

project work over credentials. A strong portfolio of real-world AI

implementations will outweigh years of experience in our evaluation.

Education

Qualification

• B.E. / B.Tech in Computer Science, IT,

Electronics, or related engineering discipline - Preferred

• BCA / MCA / B.Sc. (Computer Science) with strong

practical AI experience - Acceptable

• No formal degree with exceptional portfolio and

demonstrated AI implementation experience - We will consider

• Relevant certifications (DeepLearning.AI, Google

Cloud AI, AWS AI/ML, Microsoft Azure AI) are a bonus, not a requirement

Benefits

Why Join Binary

You'll work on real problems, not demos.

Our clients are live businesses - D2C brands, enterprise

operations teams, retail chains - with real data, real pressure, and real

budgets. Your work ships and impacts their business.

You'll own your domain.

This isn't a support role. You'll be the AI Architect - with

the authority and responsibility to make meaningful technical decisions.

You'll stay ahead of the curve.

Binary invests in tool licenses, GPU access, and learning

budgets. You'll experiment with the latest models and frameworks, not just

maintain legacy integrations.

Privacy-first AI is our differentiation.

We believe in giving clients the choice between cloud and

on-premise AI. You'll build solutions that respect data sovereignty - a growing

need in India's enterprise market.

You'll grow with the practice, not just in it.

AI is Binary's fastest-growing vertical. The person in this

role today shapes what the team looks like in two years.

Growth Opportunity

Timeline

Role & Scope

Now

AI Solutions Architect -

Design and implement AI systems across client engagements

12-18 Months

Senior AI Solutions

Architect - Larger clients, more complex architectures, team influence

24-36 Months

AI Practice Lead / Head of

AI Solutions - Own the practice, build the team, shape Binary's AI product IP

Company Culture

• Builders over buzzword followers - We respect

people who ship, not people who theorize

• Experimentation is encouraged - We'd rather you

try something new and learn than play it safe every time

• Clients are partners - We don't disappear after

delivery; we build long-term relationships

• Continuous learning is the norm - The team

shares releases, experiments, and learnings regularly

• Flat, direct communication - No layers of

bureaucracy; you can reach founders and senior leadership with a message

• Outcomes over optics - We measure by what got

built and what it achieved, not by meeting attendance or long hours