ai systems engineer

My Digital People

AI Engineer &ndash; Generative, Agentic AI &amp; AutomationWe&rsquo;re looking for a hands-on AI Engineer (2&ndash;3 years experience) who can design, build, and scale AI-powered automations and agentic systems. This role focuses on practical implementation &mdash; from intelligent workflows and voice agents to deploying open-source models on cloud infrastructure.You&rsquo;ll work on end-to-end automation systems that streamline business processes using AI.Key ResponsibilitiesAI Automation &amp; Workflows (Core Focus)<ul><li>Design and build end-to-end AI automations for business processes</li><li>Create intelligent workflows using n8n, Make, Zapier, Flowise, and custom Python</li><li>Automate tasks such as lead handling, customer support, data processing, and reporting</li><li>Connect multiple systems (CRMs, databases, APIs) into seamless automated pipelines</li><li>Build event-driven and trigger-based automation systems</li></ul>Agentic AI Systems<ul><li>Develop agentic workflows using LangChain, LangGraph, or similar tools</li><li>Architect multi-agent systems with task delegation and decision-making</li><li>Enable agents to interact with tools, APIs, and real-world data</li></ul>AI Systems &amp; Integrations<ul><li>Build AI applications across chat, voice, image, and video</li><li>Integrate AI with external tools using APIs, MCP, and webhooks</li><li>Orchestrate multiple AI providers (OpenAI, Anthropic, Google, open-source)</li></ul>Voice AI<ul><li>Develop and deploy voice agents using Vapi, ElevenLabs, or similar platforms</li><li>Design real-time conversational experiences</li></ul>RAG &amp; Knowledge Systems<ul><li>Build and maintain knowledge bases and RAG pipelines</li><li>Handle document ingestion, chunking, and embedding workflows</li></ul>Deployment &amp; Infrastructure<ul><li>Deploy and manage open-source models on cloud platforms (AWS, Azure, GCP)</li><li>Work with Docker and basic Kubernetes</li><li>Ensure scalability, monitoring, and cost control</li></ul>Prompt Engineering &amp; System Design<ul><li>Design robust prompts and multi-turn AI systems</li><li>Optimize context handling and response accuracy</li></ul>Evaluation &amp; Optimization<ul><li>Build evaluation frameworks (LLM-as-judge, human review)</li><li>Implement logging and observability (LangSmith, Helicone, or similar tools)</li><li>Optimize performance and cost through caching and model routing</li></ul>Security &amp; Reliability<ul><li>Implement AI guardrails (prompt injection protection, PII handling)</li><li>Ensure safe, reliable, and production-ready deployments</li></ul>Required Skills &amp; Experience<ul><li>2&ndash;3 years of experience in AI/ML, automation engineering, or AI-driven development</li><li>Strong Python skills</li><li>Hands-on experience with automation tools (n8n, Make, Zapier, or similar)</li><li>Experience building AI automations or workflow systems</li><li>Familiarity with LangChain, LangGraph, or similar frameworks</li><li>Strong understanding of APIs, webhooks, and system integrations</li><li>Experience with cloud platforms (AWS, Azure, or GCP)</li><li>Knowledge of prompt engineering and AI system design</li><li>Understanding of AI system evaluation, logging, and debugging</li></ul>Nice to Have<ul><li>Experience with vector databases (Pinecone, FAISS, Weaviate, Qdrant)</li><li>Familiarity with AI development tools (Cursor, Claude Code)</li><li>Experience with voice/telephony or real-time systems</li><li>Exposure to fine-tuning techniques (LoRA, QLoRA)</li><li>Experience with business process automation (BPA) systems</li></ul>EducationBachelor&rsquo;s degree in Computer Science, Engineering, Data Science, or equivalent practical experience.Job Type: Full-timeWork Location: In person

Automation Engineer (n8n & Zapier)+Model Training

Hustech

hustech.ai builds production-ready AI systems for real businesses. We work with international clients across automation, NLP, Computer Vision, LLM applications, and custom AI products. Our focus is delivery, reliability, and real business outcomes.Role OverviewWe are hiring an experienced Applied AI Engineer who can take ownership of client projects from start to finish.This is not a research-only role and not for fresh graduates. We need someone who can understand client requirements, design the right solution, build the system, deploy it, and support delivery.You should be comfortable handling different AI project types such as ML, Deep Learning, NLP, Computer Vision, LLM apps, RAG systems, and AI agents.What You&rsquo;ll Do<ul><li>Join client calls and convert requirements into technical solutions</li><li>Design end-to-end AI system architecture</li><li>Build and train ML / DL models</li><li>Develop NLP, CV, LLM, RAG, and agent-based systems</li><li>Build APIs and backend services using Python / FastAPI</li><li>Deploy solutions using Docker and cloud platforms</li><li>Integrate AI systems into client products and workflows</li><li>Optimize performance, accuracy, and scalability</li><li>Debug issues and deliver production-ready systems</li><li>Communicate progress clearly with international clients</li></ul>Required Experience<ul><li>3+ years professional industry experience (real client work, not coursework)</li><li>Proven experience delivering end-to-end AI projects</li><li>Strong Python skills</li><li>Hands-on experience in several of these areas: ML, DL, NLP, CV, LLMs, RAG, Agents etc</li><li>Experience with PyTorch or TensorFlow</li><li>Experience with APIs, FastAPI, Docker, deployment</li><li>Strong problem-solving and system design skills</li><li>Good spoken and written English</li><li>Comfortable speaking with international clients</li></ul>Preferred Skills<ul><li>AWS, GCP, or Azure</li><li>Vector databases (Qdrant, Pinecone, Weaviate)</li><li>OpenCV, Hugging Face, Scikit-learn</li><li>Automation tools and workflow systems</li></ul>Who Should ApplyApply only if you have already built and delivered real AI systems for companies or clients and can work independently with ownership.EducationBachelor&rsquo;s or Master&rsquo;s in Computer Science, AI, Machine Learning, or related field.Job Type: Full-timeExperience:<ul><li>AI Engineer: 3 years (Required)</li></ul>Language:<ul><li>English (Required)</li></ul>Work Location: In person

AI/ML Engineer

Contour Software

<div>
 
 About Contour
 
 
 
 Contour Software has grown from a dozen people to over 2,000 staff across 3 cities, in less than 14 years.
 
 
 As a subsidiary of Constellation Software Inc., we are proud to be part of a global enterprise software conglomerate that has grown to become one of the top 10 software companies in the world, with employees and customers in 100+ countries. With a broad-based and ever-growing portfolio of market-leading, vertical-market enterprise solutions covering more than 100 industry domains in predominantly mature markets, CSI's recipe creates the perfect environment for professionals to build fulfilling, long-term careers.
 
 
 What started as an R&amp;D &amp; Accounting back-office, has progressed into a full-service Global Centre serving all functions and departments, at the divisional as well as operating group/corporate level. Today Contour employees, located in Karachi, Lahore &amp; Islamabad, are serving CSI divisions located in time zones spanning the globe, from Sydney to Vancouver. With the global growth of Constellation as the wind in our sails, we are only just getting started!
 
 
 
 Job Description: AI Engineer - DIS
 
 
 
 
 The Division
 
 
 
 Dealer Information Systems Corporation (Client) is a leading business management software provider to agricultural, construction, truck refrigeration and lift truck dealers in North America. Founded in 1980, and based in Bellingham WA (USA); we are a team of 100+ professionals who help customers with Software, Hardware and Network Management so they don't have to deal with many vendors but just one full-service company.
 
 
 Division Profile: https://www.discorp.com/
 
 
 
 The Position
 
 
 
 The division is seeking a
 
 AI Engineer
 
 to join its team. This individual will be responsible for designing and developing the AI platform, including building GenAI systems from the ground up, creating production-ready retrieval-augmented generation (RAG) solutions, developing semantic search and embeddings pipelines, and architecting advanced LLM orchestration layers for complex workflows and agentic systems.
 
 
 The chosen individual will work out of the Contour Software Lahore or Islamabad resource center office as an extension of the division-based R&amp;D department.
 
 
 
 Essential Duties And Responsibilities
 
 
 
 <ul>
 <li>
 AI Platform Architecture:
 </li>
 <li>
 Design and implement the enterprise GenAI architecture from the ground up.
 </li>
 <li>
 Build production-ready RAG systems, semantic search pipelines, embeddings workflows, and vector data infrastructure.
 </li>
 <li>
 Architect LLM orchestration layers for multi-step reasoning, tool usage, and AI-driven workflows.
 </li>
 <li>
 Define scalable patterns for agentic systems and domain-aware assistants.
 </li>
 <li>
 LLM Systems in Production:
 </li>
 <li>
 Integrate LLM providers (OpenAI, Anthropic, open-weight models, or hybrid approaches) into secure, observable enterprise systems.
 </li>
 <li>
 Build AI service layers, orchestration APIs, caching, evaluation pipelines, and monitoring frameworks.
 </li>
 <li>
 Design for latency, cost optimization, safety, and reliability at scale.
 </li>
 <li>
 Establish measurable quality benchmarks and evaluation strategies for AI outputs.
 </li>
 <li>
 Responsible &amp; Enterprise-Ready AI:
 </li>
 <li>
 Implement guardrails, policy enforcement, and hallucination mitigation mechanisms.
 </li>
 <li>
 Define governance standards for data provenance, auditability, and transparency.
 </li>
 <li>
 Build AI systems that engineering and compliance teams can trust.
 </li>
 <li>
 AI Adoption &amp; Enablement:
 </li>
 <li>
 Translate high-impact business problems into AI-native architectures.
 </li>
 <li>
 Partner with product leaders to prioritize AI features that drive measurable value.
 </li>
 <li>
 Mentor engineers and raise the organization&rsquo;s AI maturity.
 </li>
 <li>
 Move teams from PoCs to scalable, production-grade AI capabilities.
 
 
 </li>
 </ul>
 
 Required Education And Experience
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Computer Science, Computer Engineering or equivalent technical Degree; or equivalent combination of education and experience.
 </li>
 <li>
 5+ years building applied AI/ML systems, with strong recent experience in Generative AI.
 </li>
 <li>
 Proven experience shipping LLM-powered applications (RAG, embeddings, prompt strategies, model adaptation).
 </li>
 <li>
 Deep understanding of vector search, semantic retrieval, and AI system evaluation.
 </li>
 <li>
 Experience building orchestration layers using frameworks such as LangChain, Semantic Kernel, LlamaIndex, or designing equivalent custom architectures.
 </li>
 <li>
 Strong cloud-native engineering experience (AWS, Azure, or GCP).
 </li>
 <li>
 Advanced Python skills and experience building scalable backend systems and APIs.
 </li>
 <li>
 Experience implementing observability, CI/CD, and monitoring for AI systems in production.
 </li>
 <li>
 Ability to balance innovation with enterprise constraints (security, compliance, reliability).
 
 
 </li>
 </ul>
 
 What Makes This Role Different
 
 
 
 <ul>
 <li>
 You are not inheriting a legacy AI stack; you will help define it.
 </li>
 <li>
 You will shape AI standards, architecture, and governance across the division.
 </li>
 <li>
 Your work will power real customer-facing products and operational intelligence.
 </li>
 <li>
 You will operate at the intersection of AI strategy, architecture, and hands-on engineering.
 
 
 </li>
 </ul>
 
 Exciting Benefits We Offer
 
 
 
 <ul>
 <li>
 Market-leading Salary
 </li>
 <li>
 Medical Coverage &ndash; Self &amp; Dependents
 </li>
 <li>
 Parents Medical Coverage
 </li>
 <li>
 Provident Fund
 </li>
 <li>
 Employee Performance-based bonuses
 </li>
 <li>
 Home Internet Subsidy
 </li>
 <li>
 Conveyance Allowance
 </li>
 <li>
 Profit Sharing Plan [Tenured Employees Only]
 </li>
 <li>
 Life Benefit
 </li>
 <li>
 Child Care Facility
 </li>
 <li>
 Company Provided Lunch/Dinner
 </li>
 <li>
 Professional Development Budget
 </li>
 <li>
 Recreational area for in-house games
 </li>
 <li>
 Sporadic On-shore training opportunities
 </li>
 <li>
 Friendly work environment
 </li>
 <li>
 Leave Encashment
 
 
 </li>
 </ul>
 
 
 Disclaimer:
 
 
 
 At Contour, we attribute our success to the unique contributions of our diverse staff. We&rsquo;re committed to fostering a culture of respect that thrives on the varied perspectives and experiences of all individuals we recruit, employ, promote, and compensate. Since day one, we&rsquo;ve adhered to a policy that champions a work environment honoring the worth and dignity of each person while being free from all forms of employment discrimination.
 
 
 
 
 In our continuous effort to promote inclusivity, we extend our commitment to individuals with special needs by providing reasonable accommodations. We actively encourage qualified individuals with special needs to apply for the various openings within our company. Should you require assistance in completing the application process or have any inquiries regarding special facilities, please do not hesitate to contact our HR team. Your unique talents and abilities are welcomed and valued here.
 
</div>

Junior AI Engineer

Friday Media Group Pakistan

<div>
 
 
 Type: Full-timeCompany: Friday Media Group (FMG)About the Role:
 
 
 
 We are building a next-generation
 
 AI Agent Platform
 
 across our group, alongside deploying specialised AI agents within our products and business wide operations. We are looking for a
 
 hands-on AI Engineer
 
 with strong experience in:
 
 <ul>
 <li>
 building and deploying AI agents
 </li>
 <li>
 designing
 
 production-grade RAG (Retrieval-Augmented Generation) systems
 
 </li>
 <li>
 working with frameworks such as
 
 LangChain and CrewAI
 
 </li>
 </ul>
 
 This is not a research role.
 
 
 We are looking for someone who has
 
 built and shipped real AI systems into production environments
 
 .
 
 
 
 
 
 
 What You Will Be Working On:
 
 
 <ul>
 <li>
 Designing and building
 
 multi-agent systems
 
 for real-world business workflows
 </li>
 <li>
 Developing agents across:
 </li>
 <li>
 Finance
 </li>
 <li>
 Customer support automation
 </li>
 <li>
 Marketing workflows
 </li>
 <li>
 Sales and CRM automation
 </li>
 <li>
 Building
 
 RAG-powered systems
 
 to enable agents to retrieve and reason over internal data
 </li>
 <li>
 Integrating AI agents with real systems:
 </li>
 <li>
 NetSuite
 </li>
 <li>
 N8N&nbsp;
 </li>
 <li>
 CRMs
 </li>
 <li>
 Email systems
 </li>
 <li>
 Internal APIs and databases
 </li>
 <li>
 Creating
 
 hybrid systems combining rules, workflows, and LLM reasoning
 
 </li>
 <li>
 Implementing structured outputs (JSON, workflows, automation triggers)
 </li>
 </ul>
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Build, test, and deploy
 
 AI agents end-to-end
 
 </li>
 <li>
 Design
 
 agent architectures
 
 (single-agent, multi-agent, tool-using agents)
 </li>
 <li>
 Develop and optimise
 
 RAG pipelines
 
 , including:
 </li>
 <li>
 document ingestion and chunking strategies
 </li>
 <li>
 embedding pipelines
 </li>
 <li>
 vector search and retrieval optimisation
 </li>
 <li>
 grounding LLM outputs with internal data
 </li>
 <li>
 Implement
 
 context management, memory, and tool usage
 
 within agents
 </li>
 <li>
 Hands on experience with N8N or similar workflow automation tools
 </li>
 <li>
 Integrate agents with external APIs, databases, and SaaS platforms
 </li>
 <li>
 Build evaluation, monitoring, and logging systems for agent performance
 </li>
 <li>
 Optimise for
 
 accuracy, latency, and cost efficiency
 
 </li>
 <li>
 Work closely with product teams to translate workflows into AI-driven systems
 </li>
 </ul>
 
 
 
 
 
 Required Skills &amp; Experience:
 
 
 <ul>
 <li>
 Strong experience in
 
 Python
 
 </li>
 <li>
 Hands-on experience with:
 </li>
 <li>
 
 LangChain
 
 </li>
 <li>
 
 CrewAI
 
 (or similar multi-agent frameworks)
 </li>
 <li>
 Proven experience building
 
 production-grade AI agents
 
 </li>
 <li>
 Strong experience with
 
 RAG systems
 
 , including:
 </li>
 <li>
 embeddings and vector search
 </li>
 <li>
 retrieval optimisation (filters, hybrid search, ranking)
 </li>
 <li>
 grounding outputs with structured and unstructured data
 </li>
 <li>
 Experience working with
 
 vector databases
 
 such as:
 </li>
 <li>
 
 Pinecone
 
 </li>
 <li>
 or alternatives (Weaviate, FAISS, etc.)
 </li>
 <li>
 Experience with LLM APIs (OpenAI, Gemini, etc.)
 </li>
 <li>
 Strong understanding of:
 </li>
 <li>
 prompt design
 </li>
 <li>
 tool/function calling
 </li>
 <li>
 memory and context handling
 </li>
 </ul>
 
 
 
 
 
 Preferred (Nice to Have):
 
 
 <ul>
 <li>
 Experience building AI agents in:
 </li>
 <li>
 Finance (AP, AR, reporting, forecasting)
 </li>
 <li>
 Marketing automation
 </li>
 <li>
 Sales / CRM workflows
 </li>
 <li>
 Customer support systems
 </li>
 <li>
 Experience with
 
 fine-tuning or adapting models
 
 , including:
 </li>
 <li>
 instruction tuning
 </li>
 <li>
 domain adaptation
 </li>
 <li>
 evaluation of fine-tuned vs prompt-based approaches
 </li>
 <li>
 Experience with advanced RAG patterns:
 </li>
 <li>
 hybrid search (vector + keyword)
 </li>
 <li>
 re-ranking models
 </li>
 <li>
 agent-driven retrieval strategies
 </li>
 <li>
 Experience with:
 </li>
 <li>
 Supabase / PostgreSQL
 </li>
 <li>
 FastAPI or similar backend frameworks
 </li>
 <li>
 event-driven or workflow-based systems
 </li>
 <li>
 Exposure to NetSuite or financial systems is a strong plus
 </li>
 </ul>
 
 
 
 
 
 What We Are Looking For:
 
 
 <ul>
 <li>
 Someone who has
 
 actually built and deployed AI agents
 
 , not just experimented
 </li>
 <li>
 Strong problem solver who can translate business workflows into AI systems
 </li>
 <li>
 Comfortable working in a
 
 fast-moving, product-driven environment
 
 </li>
 <li>
 Ability to balance:
 </li>
 <li>
 LLM reasoning
 </li>
 <li>
 deterministic rules
 </li>
 <li>
 system design
 </li>
 </ul>
 
 
 Important Note
 
 
 
 We are not looking for basic &ldquo;chat with documents&rdquo; implementations.
 
 
 We are building
 
 production-grade AI systems integrated with real business workflows and decision engines
 
 .
 
 
 
 
 
 
 Why Join Us:
 
 
 <ul>
 <li>
 Work on
 
 real-world AI deployment
 
 , not just prototypes
 </li>
 <li>
 Build systems that directly impact business operations
 </li>
 <li>
 Opportunity to shape a
 
 group-wide AI platform (FridayOS vision)
 
 </li>
 <li>
 Exposure to multiple domains: finance, marketplaces, SaaS, recruitment
 </li>
 </ul>
</div>

Senior AI Engineer – Agent Systems & RAG (LangChain / CrewAI / Python / N8N)

We are seeking a highly motivated and hands-on AI Engineer with 2&ndash;3 years of experience in building, deploying, and maintaining AI-powered systems and workflows. This role focuses on practical implementation across Generative AI, Agentic Automation, Voice AI, and Open-Source Model Deployment.The ideal candidate will have experience designing intelligent automation pipelines, deploying AI models in cloud environments, and rapidly adapting to new AI tools, frameworks, and emerging technologies. You will collaborate closely with cross-functional teams to deliver scalable, production-ready AI solutions.Key ResponsibilitiesAgentic AI &amp; Workflow Automation<ul><li>Design and build agentic AI workflows and automation pipelines using frameworks such as LangChain, LangGraph, and similar tools.</li><li>Architect multi-agent systems where multiple AI agents collaborate, delegate tasks, and execute complex workflows autonomously.</li><li>Develop AI-powered automation systems using no-code/low-code platforms including n8n, Make, Flowise, alongside custom Python development.</li></ul>Voice AI Development<ul><li>Build and deploy voice agents using tools such as Vapi, ElevenLabs, or comparable platforms.</li><li>Integrate speech-to-text (STT), text-to-speech (TTS), and conversational voice capabilities into AI solutions.</li></ul>Model Deployment &amp; Infrastructure<ul><li>Deploy, host, and maintain open-source AI models for chat, voice, image, and video generation on cloud/GPU infrastructure.</li><li>Fine-tune open-source models using LoRA / QLoRA for domain-specific applications.</li><li>Manage cloud environments including provisioning, scaling, monitoring, and cost optimization.</li></ul>RAG / Knowledge Base Management<ul><li>Design and maintain knowledge bases and data pipelines, including:</li><li>Document ingestion and processing</li><li>Chunking strategies</li><li>Embedding pipelines</li><li>RAG source management and freshness</li></ul>Prompt Engineering &amp; AI Architecture<ul><li>Craft production-grade prompts and system prompts for reliable AI outputs.</li><li>Design multi-turn conversational flows and optimize context window management.</li><li>Select and orchestrate appropriate AI models across providers (OpenAI, Anthropic, Google, Open Source) based on use-case requirements.</li></ul>Testing, Evaluation &amp; Monitoring<ul><li>Build evaluation/testing pipelines for AI outputs, including:</li><li>LLM-as-Judge frameworks</li><li>Human evaluation workflows</li><li>Prompt regression testing</li><li>Set up observability/logging systems using tools such as LangSmith, Helicone, or custom monitoring solutions.</li><li>Monitor agent performance, trace failures, and improve output quality over time.</li></ul>Security &amp; Optimization<ul><li>Implement AI security guardrails, including:</li><li>Prompt injection mitigation</li><li>Output filtering</li><li>PII protection</li><li>Safe-by-default AI architecture</li><li>Optimize inference costs using:</li><li>Token management</li><li>Caching strategies</li><li>Smart model routing</li></ul>Engineering Best Practices<ul><li>Contribute to CI/CD pipelines and maintain clean, scalable, production-ready codebases.</li><li>Collaborate with teams to integrate AI solutions into products and business processes.</li><li>Continuously explore and integrate emerging AI tools, models, and frameworks.</li></ul>Required Skills &amp; ExperienceExperience<ul><li>2&ndash;3 years of experience in AI/ML systems, AI-focused software engineering, or related technical roles.</li><li>Proven experience building and deploying AI-powered systems in production.</li></ul>AI &amp; Automation<ul><li>Hands-on experience with:</li><li>Agentic AI workflows</li><li>AI automation pipelines</li><li>Multi-agent architectures</li><li>Task delegation patterns</li></ul>Programming &amp; Frameworks<ul><li>Strong proficiency in Python</li><li>Experience with:</li><li>LangChain / LangGraph / Similar orchestration frameworks</li><li>REST APIs / Webhooks / Microservices</li><li>MCP (Model Context Protocol) for tool/service integrations</li></ul>Voice AI<ul><li>Experience with:</li><li>Vapi</li><li>ElevenLabs</li><li>Other voice/conversational AI platforms</li></ul>Deployment &amp; Infrastructure<ul><li>Ability to deploy/serve:</li><li>Open-source LLMs</li><li>Image/Video Generation Models</li><li>TTS/STT Models</li><li>Experience with:</li><li>Docker</li><li>Basic Kubernetes</li><li>GPU/cloud hosting environments</li></ul>Fine-Tuning / Optimization<ul><li>Familiarity with:</li><li>LoRA / QLoRA</li><li>Model customization techniques</li></ul>Evaluation &amp; Testing<ul><li>Experience building:</li><li>AI evaluation pipelines</li><li>Prompt testing/regression systems</li></ul>Security<ul><li>Understanding of:</li><li>Prompt injection defense</li><li>Output moderation/filtering</li><li>PII handling</li></ul>Cloud Platforms<ul><li>Experience with:</li><li>Azure / AWS / GCP</li><li>Understanding of:</li><li>Hosting</li><li>Scaling</li><li>Monitoring</li><li>Cost control</li></ul>Observability<ul><li>Familiarity with:</li><li>LangSmith</li><li>Helicone</li><li>AI tracing/debugging tools</li></ul>Knowledge Base / RAG<ul><li>Strong understanding of:</li><li>Embedding pipelines</li><li>Vector search</li><li>Chunking/document strategies</li><li>RAG maintenance</li></ul>Nice to Have<ul><li>Experience with Vector Databases:</li><li>Pinecone, FAISS, Weaviate, Qdrant</li><li>Familiarity with:</li><li>Claude Code / Cursor / AI-assisted development tools</li><li>Experience with:</li><li>ComfyUI / Stable Diffusion / Open-source image-video generation</li><li>Knowledge of:</li><li>WebSockets / Real-time Streaming / Telephony Integrations</li><li>Exposure to:</li><li>Azure ML / Databricks / Distributed Training / Mixed Precision (fp16)</li><li>Understanding of:</li><li>Responsible AI / Governance Practices</li></ul>Education<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, Data Science, or related field</li><li>OR equivalent practical experience</li></ul>Job Type: Full-timeWork Location: In person

Senior AI Engineer

Skylinx Technologies

AI Engineer &ndash; Lahore (On-Site)We are hiring an in-house AI Engineer to join our Lahore-based engineering team. This role focuses on building and deploying AI-driven features for our custom platform, including data intelligence, competitive alerts, and user-facing AI interfaces. You will work closely with backend and product teams and have direct ownership of AI integrations and deployments.Key Responsibilities<ul><li>Work with existing machine learning models and large language models (LLMs).</li><li>Deploy and manage AI/ML models on private cloud or self-hosted infrastructure.</li><li>Integrate third-party AI tools and APIs (e.g., Groq, OpenAI, Hugging Face, vector databases).</li><li>Build data pipelines by connecting AI models with relational and NoSQL databases.</li><li>Design and implement competitive alerts, insights, and notifications from structured and unstructured data.</li><li>Develop APIs and basic interfaces to expose AI capabilities within the platform.</li><li>Optimize inference performance, cost, and scalability.</li><li>Ensure data security and privacy in AI workflows.</li><li>Collaborate closely with in-house backend, frontend, and product teams.</li></ul>Required Skills &amp; Qualifications<ul><li>2+ years of professional experience in AI/ML engineering or applied AI development.</li><li>Strong proficiency in Python.</li><li>Hands-on experience with machine learning models, LLMs, or inference pipelines.</li><li>Experience deploying models on private cloud, VPS, or on-prem infrastructure.</li><li>Familiarity with third-party AI platforms and tools (e.g., Groq, OpenAI, Anthropic).</li><li>Experience working with databases (MySQL, PostgreSQL, MongoDB, etc.).</li><li>Ability to build and consume REST APIs.</li><li>Basic experience with interfaces or dashboards for AI-powered features.</li><li>Strong problem-solving skills and ability to work in an on-site team environment.</li></ul>Nice to Have<ul><li>Experience with RAG (Retrieval-Augmented Generation) systems.</li><li>Knowledge of alerting systems, recommendation engines, or analytics dashboards.</li><li>Familiarity with Docker, Kubernetes, or MLOps workflows.</li><li>Experience in SaaS or data-driven platforms.</li><li>Frontend exposure (React, Vue, or similar).</li></ul>What We Offer<ul><li>On-site role in Lahore with a collaborative engineering team.</li><li>Opportunity to build production-grade AI systems.</li><li>Competitive salary</li><li>Long-term growth and learning opportunities.</li><li>Direct impact on core product features.</li></ul>How to ApplyPlease share:<ul><li>Your updated resume</li><li>GitHub or project links (if available)</li><li>Short summary of AI or ML projects you&rsquo;ve worked on</li></ul>Work Location: In person

AI Engineer (In-House)

NorthBay - Pakistan

<div>
 
 Role: Team Lead - Azure AI (Agentic) Engineer
 
 
 
 
 Location:
 
 Pakistan (hybrid work model)
 
 
 
 
 Client: Middle East (Government)
 
 
 
 
 
 About The Role
 
 
 
 NorthBay Solutions, an AWS global Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber
 
 Azure AI Specialist (Team Lead)
 
 with deep expertise in building enterprise-grade
 
 Generative AI, RAG, and Agentic AI solutions
 
 on the Azure ecosystem.
 
 
 This role requires hands-on experience in designing scalable, multi-tenant AI systems, integrating LLMs, and building intelligent pipelines using Azure-native services.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and deploy LLM-powered applications using Azure OpenAI for enterprise use cases
 </li>
 <li>
 Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search (vector + hybrid search)
 </li>
 <li>
 Develop Agentic AI systems leveraging frameworks and tool-based reasoning approaches
 </li>
 <li>
 Implement custom Document Intelligence models for high-accuracy data extraction (e.g., IDs, structured documents)
 </li>
 <li>
 Architect multi-tenant AI deployments with scalability, security, and cost-efficiency in mind
 </li>
 <li>
 Develop and manage Knowledge Graphs for structured reasoning and contextual intelligence
 </li>
 <li>
 Apply advanced prompt engineering techniques (Few-shot, Chain-of-Thought, ReAct)
 </li>
 <li>
 Use Prompt Flow in Azure AI Studio for experimentation, testing, and versioning
 </li>
 <li>
 Design intelligent conversational systems with fallback handling and contextual memory
 </li>
 <li>
 Build and manage MLOps pipelines using Azure Machine Learning
 
 
 </li>
 </ul>
 
 Required Skills &amp; Experience
 
 
 
 <ul>
 <li>
 Overall 10+ years experience, with a focus on Azure OpenAI API (deployments, scaling, optimization)
 </li>
 <li>
 Proven expertise in building RAG pipelines using Azure AI Search
 </li>
 <li>
 Experience with vector databases and hybrid search architectures
 </li>
 <li>
 Practical experience in Agentic AI / multi-agent systems
 </li>
 <li>
 Hands-on with Azure AI Document Intelligence (Form Recognizer)
 </li>
 <li>
 Solid understanding of Knowledge Graphs and semantic modeling
 </li>
 <li>
 Expertise in prompt engineering &amp; LLM optimization techniques
 </li>
 <li>
 Experience with Prompt Flow (Azure AI Studio)
 </li>
 <li>
 Strong background in Python and cloud-native development
 </li>
 <li>
 Experience with Azure ML / MLOps pipelines
 </li>
 <li>
 Ability to design scalable and secure enterprise AI architectures
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with LangChain, Semantic Kernel, or similar frameworks
 </li>
 <li>
 Exposure to multi-agent orchestration tools
 </li>
 <li>
 Prior experience working with enterprise clients or large-scale AI deployments
 </li>
 </ul>
</div>

Azure AI (Agentic) Specialist - Team Lead

Explore 726+ Ai systems engineer in Lahore this April. Find roles across top companies and apply now to boost your career.