AI Engineer

Smctechsolutions; Haripur; On-site; PKR 1,800,000 - 3,000,000; Full time

Job summary

Smctechsolutions is seeking an experienced AI engineer to design and ship intelligent workflows and agent behaviours deployed to live client environments from day one. You will work closely with RiverAI delivery engineers and the Pod Zero QA Tester within a cross-project capability team serving multiple clients.

You’ll design prompts, route tasks across LLMs, and deploy agents across Azure AI and AWS Bedrock, while integrating with APIs, vector databases, and RAG pipelines.

Qualifications

• 3+ years in AI engineering, automation, or workflow development.
• Hands-on experience with OneReach.ai or a comparable orchestration platform.
• Prompt engineering across multiple LLMs — not limited to a single model.
• API and webhook integration experience with structured data handling.
• Containerisation with Docker.
• Multi-agent design — routing, fallback, and coordination patterns.
• Clear communicator who can explain a complex technical design in plain language.
• Experience deploying on Azure AI and/or AWS Bedrock.
• Vector database and RAG pipeline design experience.
• Familiarity with RPA/BPM tools such as UiPath or enterprise integration patterns.
• Model evaluation and cost/performance optimisation across providers.
• Awareness of AI safety standards — EU AI Act, ISO 42001, or NIST AI RMF.

Responsibilities

• Design and deploy intelligent workflows and agent behaviours in OneReach.ai.
• Route tasks across LLMs based on cost, capability, and context requirements.
• Build and optimise prompts, context windows, and memory architectures per model.
• Deploy agents across Azure AI and AWS Bedrock depending on client infrastructure.
• Integrate agents with APIs, vector databases, RAG pipelines, RPA tools, and enterprise platforms.
• Implement human-in-the-loop and AI-in-the-loop patterns for safe, explainable operation.
• Support live AI Operations engagements — monitor, improve, and scale deployed agents.
• Contribute to reusable patterns, playbooks, and multi-model prompt libraries for the wider team.

Skills

AI engineering

Automation

Workflow development

Communication

Tools

OneReach.ai

Docker

Azure AI

AWS Bedrock

UiPath

Job description

This is a production engineering role — not prototyping, not research. You’ll design and ship intelligent workflows and agent behaviours that run in live client environments from day one, working as part of Pod Zero, a cross-project shared capability team serving multiple clients.

You’ll work closely with RiverAI delivery engineers and the Pod Zero QA Tester, pulling work from a shared pod backlog and contributing directly to the systems our clients depend on. If you want to build AI that actually gets used — this is that role.

What You'll Do

• Design and deploy intelligent workflows and agent behaviours in OneReach.ai
• Route tasks across LLMs based on cost, capability, and context requirements
• Build and optimise prompts, context windows, and memory architectures per model
• Deploy agents across Azure AI and AWS Bedrock depending on client infrastructure
• Integrate agents with APIs, vector databases, RAG pipelines, RPA tools, and enterprise platforms
• Implement human-in-the-loop and AI-in-the-loop patterns for safe, explainable operation
• Support live AI Operations engagements — monitor, improve, and scale deployed agents
• Contribute to reusable patterns, playbooks, and multi-model prompt libraries for the wider team

What We're Looking For

• Required
• 3+ years in AI engineering, automation, or workflow development
• Hands-on experience with OneReach.ai or a comparable orchestration platform
• Prompt engineering across multiple LLMs — not limited to a single model
• API and webhook integration experience with structured data handling
• Containerisation with Docker
• Multi-agent design — routing, fallback, and coordination patterns
• Clear communicator who can explain a complex technical design in plain language
• Experience deploying on Azure AI and/or AWS Bedrock
• Vector database and RAG pipeline design experience
• Familiarity with RPA/BPM tools such as UiPath or enterprise integration patterns
• Model evaluation and cost/performance optimisation across providers
• Awareness of AI safety standards — EU AI Act, ISO 42001, or NIST AI RMF

Tools & Technologies

Technologies, platforms, and tools you’ll be working with.