ai workflow engineer

Luxoft

<div><div><h5 class="jobSectionHeader"><b>Project description
</b></h5><p>We are seeking a Palantir Foundry &amp; AIP Engineer with hands-on experience across the full Foundry ecosystem and Palantir&rsquo;s Artificial Intelligence Platform (AIP). This role goes beyond data engineering: you will design, build, and operationalize AI-powered workflows, agents, and applications that drive tangible business outcomes. The ideal candidate is a self-starter, able to translate complex business needs into scalable technical solutions, and confident working directly with stakeholders to maximize the value of Foundry and AIP.
</p></div><div><h5 class="jobSectionHeader"><b>Responsibilities</b></h5>
<div><div><ul><li>Data &amp; Workflow Engineering: Design, develop, and maintain scalable pipelines, transformations, and applications within Palantir Foundry.
</li></ul></div><div><ul><li>AIP &amp; AI Enablement:
</li></ul></div><div><p>Support the design and deployment of AIP use cases such as copilots, retrieval workflows, and decision-support agents.
</p></div><div><p>Ground agents and logic flows using RAG (retrieval‐augmented generation) by connecting to relevant data sources, embedding/vector search, ontology content.
</p></div><div><p>Use Ontology-Augmented Generation (OAG) when needed: operational decision making where logic, data, actions and relationships are embedded in the Ontology.
</p></div><div><p>Collaborate with senior engineers on agent design, instructions, and evaluation using AIP&rsquo;s native features.
</p></div><div><ul><li>End-to-End Delivery: Work with stakeholders to capture requirements, design solutions, and deliver working applications.
</li></ul></div><div><ul><li>User Engagement: Provide training and support for business teams adopting Foundry and AIP.
</li></ul></div><div><ul><li>Governance &amp; Trust: Ensure solutions meet standards for data quality, governance, and responsible use of AI.
</li></ul></div><div><ul><li>Continuous Improvement: Identify opportunities to expand AIP adoption and improve workflow automation.
</li></ul></div></div></div><div><h5 class="jobSectionHeader"><b>Skills</b></h5>
<p>Must have
</p><div><div><p>Minimum 10 Years of experience in IT/Data.
</p></div><div><p>Minimum 5 years of experience as a Data Platform Engineer/Data Engineer.
</p></div><div><ul><li>2+ years of professional experience with the Palantir Foundry ecosystem (data integration, ontology, pipelines, applications).
</li></ul></div><div><ul><li>Strong technical skills in Python, PySpark, SQL, and data modelling.
</li></ul></div><div><ul><li>Practical experience using or supporting AIP features such as RAG workflows, copilots, or agent-based applications.
</li></ul></div><div><ul><li>Ability to work independently and engage directly with non-technical business users.
</li></ul></div><div><ul><li>Strong problem-solving mindset and ownership of delivery.
</li></ul></div></div><p>Nice to have
</p><div><div><ul><li>Familiarity with AIP Agent Studio concepts (agents, instructions, tools, testing).
</li></ul></div><div><ul><li>Exposure to AIP Evals and evaluation/test-driven approaches.
</li></ul></div><div><ul><li>Experience with integration patterns (APIs, MCP, cloud services).
</li></ul></div><div><ul><li>Consulting or applied AI/ML background.
</li></ul></div><div><ul><li>Experience in Abu Dhabi or the broader MENA region.
</li></ul></div></div></div><div><h5 class="jobSectionHeader"><b>Other</b></h5>
<div><div><div><p>Languages</p>
<p>English: C1 Advanced
</p></div></div><div><div><p>Seniority</p>
<p>Senior</p></div></div></div></div></div>
<br><div><div><div><p>Remote Turkey, Turkiye
</p></div><p>Req. VR-122803
</p></div><div></div><div><div><p>Python
</p></div><div><p>BCM Industry</p>
</div><div><p>12/06/2026
</p></div><div><p>Req. VR-122803</p></div></div></div><p></p>

Palantir Foundry Engineer

JODAYN

<div><p>Jodayn is seeking a highly skilled Senior AI Product Engineer to lead the design, development, and deployment of enterprise-grade artificial intelligence solutions and intelligent automation platforms.</p><p>
The successful candidate will play a critical role in developing scalable AI-powered products and reusable enterprise AI services that support digital transformation, governance automation, proposal evaluation, intelligent document processing, and enterprise workflow optimisation.</p><p>
This role requires a strong engineering mindset combined with hands-on experience in modern AI frameworks, large language model integration, AI orchestration, backend engineering, and enterprise solution development.</p><p>
The ideal candidate must be capable of independently designing and delivering production-ready AI systems in fast-paced enterprise environments.</p><b><br>
Requirements</b><p><br>
AI Platform Engineering</p><ul><li>
Design, develop, and maintain scalable enterprise AI platforms and intelligent automation solutions</li><li>
Build modular and reusable AI services and APIs</li><li>
Develop AI-powered workflow automation systems and intelligent orchestration pipelines</li><li>
Design and implement scalable backend architectures supporting AI workloads</li></ul><p></p><p>
Agentic AI Development</p><ul><li>
Build autonomous and semi-autonomous AI agents</li><li>
Develop multi-agent orchestration workflows and task delegation systems</li><li>
Implement memory management and contextual reasoning capabilities</li><li>
Integrate AI systems with external tools, APIs, and enterprise applications</li></ul><p></p><p>
Large Language Model Integration</p><ul><li>
Integrate and optimise large language model services including Claude, OpenAI, and open-source models</li><li>
Develop prompt orchestration pipelines and retrieval-augmented generation architectures</li><li>
Implement vector database integration and semantic search capabilities</li><li>
Optimise model performance, response quality, and operational efficiency</li></ul><p></p><p>
Enterprise System Integration</p><ul><li>
Integrate AI platforms with enterprise systems, collaboration tools, and document repositories</li><li>
Develop secure API integration patterns</li><li>
Support authentication and identity integration requirements</li><li>
Build AI-enabled enterprise workflow capabilities</li></ul><p></p><p>
Proposal &amp; Compliance Automation</p><ul><li>
Develop intelligent proposal generation and evaluation systems</li><li>
Build compliance validation and document inspection workflows</li><li>
Implement AI-assisted scoring and recommendation engines</li><li>
Support enterprise governance automation initiatives</li></ul><p></p><p>
Infrastructure &amp; Deployment</p><ul><li>
Deploy AI applications in cloud, hybrid, and on-premise environments</li><li>
Configure logging, observability, monitoring, and operational diagnostics</li><li>
Support containerisation and deployment automation practices</li><li>
Optimise infrastructure scalability and operational cost efficiency</li></ul><p></p><p><br>
Required Qualifications</p><p>
Education</p><ul><li>
Bachelor&rsquo;s degree in Computer Science, Software Engineering, Artificial Intelligence, or related field</li><li>
Master&rsquo;s degree is preferred but not mandatory</li></ul><p></p><p>
Experience</p><ul><li>
Minimum 7 years of software engineering experience</li><li>
Minimum 3 years practical experience developing AI-powered applications</li><li>
Proven experience building and deploying production-grade AI systems</li><li>
Experience working in enterprise or regulated environments preferred</li></ul><p></p><p>
Required Technical Skills</p><p>
Programming &amp; Backend Development</p><ul><li>
Python</li><li>
FastAPI or equivalent backend frameworks</li><li>
RESTful APIs</li><li>
PostgreSQL or equivalent databases</li><li>
Git and version control systems</li></ul><p>
AI Technologies</p><ul><li>
Claude APIs</li><li>
OpenAI APIs</li><li>
LangGraph</li><li>
LangChain</li><li>
Retrieval-Augmented Generation</li><li>
Vector databases</li><li>
Prompt orchestration</li><li>
AI workflow automation</li></ul><p>
Frontend &amp; Integration</p><ul><li>
React or Next.js</li><li>
API integration</li><li>
Authentication and access control concepts</li></ul><p>
Infrastructure &amp; DevOps</p><ul><li>
Docker</li><li>
Linux environments</li><li>
CI/CD pipelines</li><li>
Cloud deployment concepts</li></ul><p>
Preferred Skills</p><ul><li>
Experience with enterprise AI governance solutions</li><li>
Experience with intelligent document processing systems</li><li>
Experience using AI-assisted development tools</li><li>
Exposure to multi-agent systems and orchestration frameworks</li><li>
Familiarity with enterprise architecture concepts</li></ul><p></p><p><br>
Core Competencies</p><ul><li>
Strong analytical and problem-solving skills</li><li>
Ability to independently deliver complex technical solutions</li><li>
Strong software design capability</li><li>
Fast execution and delivery orientation</li><li>
Excellent communication and documentation skills</li><li>
Ability to work in fast-paced enterprise environments</li></ul></div><p></p>

Senior AI Product Engineer

Datamatics Global Services Ltd

<div><b>Position Title : AI/ML Engineer &ndash; Agentic AI</b><br>
<b>Experience Required: </b>4&ndash;6 Years (Should be open to Travel)<br>
<b>Employment Type : </b>Full-Time - Riyadh - Onsite<br>
<br>
<b>Job Overview</b><br>
We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions. The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.<br>
The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.<br>
<br>
<b>Key Responsibilities</b><ul><li>
Design, develop, and deploy AI/ML solutions for real-world business use cases.</li><li>
Build and optimize <b>Agentic AI systems</b> using LLMs, autonomous workflows, and multi-agent architectures.</li><li>
Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.</li><li>
Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies.</li><li>
Integrate AI agents with APIs, databases, enterprise systems, and third-party tools.</li><li>
Fine-tune, evaluate, and optimize Large Language Models (LLMs).</li><li>
Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations.</li><li>
Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.</li><li>
Perform prompt engineering, model experimentation, and performance optimization.</li><li>
Ensure AI solutions are production-ready, scalable, secure, and cost-efficient.</li><li>
Monitor model performance, drift, and continuous improvement processes.</li><li>
Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.</li></ul><b>
Required Skills &amp; Expertise</b><ul><li>
Strong hands-on experience in <b>Machine Learning, Generative AI, and Agentic AI development</b>.</li><li>
Proficiency in Python and AI/ML development frameworks.</li><li>
Experience with:<ul><li>
LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks</li><li>
OpenAI, Anthropic, Gemini, or open-source LLMs</li><li>
RAG architectures and Vector Databases</li><li>
Prompt Engineering &amp; AI workflow automation</li></ul></li><li>
Solid understanding of:<ul><li>
NLP concepts</li><li>
ML algorithms and model evaluation</li><li>
Deep Learning fundamentals</li><li>
AI model deployment and inference optimization</li></ul></li><li>
Experience with ML libraries/frameworks such as:<ul><li>
PyTorch</li><li>
TensorFlow</li><li>
Scikit-learn</li><li>
Hugging Face Transformers</li></ul></li><li>
Experience with cloud platforms such as Azure, AWS, or GCP is preferred.</li><li>
Familiarity with Docker, APIs, CI/CD, and MLOps practices.</li><li>
Strong problem-solving and analytical skills.</li></ul><b>
Preferred Qualifications</b><ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related field.</li><li>
Experience working on enterprise AI automation or AI assistant platforms is highly preferred.</li><li>
Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.</li></ul><br>
<p>
</p><p>tTAmIvfFVv</p></div>

AI/ML Engineer – Agentic AI

Deeplight

<p></p><div><p>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.</p><p>
At DeepLight, we don't believe in &quot;off-the-shelf&quot; fixes. We deliver tailored AI solutions designed to integrate seamlessly into existing enterprise architectures, ensuring that innovation is both scalable and secure. From building robust data foundations to deploying sophisticated AI platforms, we empower our clients to lead in an increasingly automated world.</p><p>
The DevOps Engineer owns the Agentic Workflow Automation (AWA) platform's deployment architecture, infrastructure-as-code (IaC), CI/CD pipelines, and continuous operational reliability. Operating within the AI Centre of Excellence (AICoE) at a Mid-level capacity, this position serves as the primary guardian of the cloud-native infrastructure within the bank's Azure UAE environment. The role ensures that every critical platform component&mdash;ranging from AKS namespaces and KEDA autoscalers to ADLS Gen2 storage lifecycles and firewall configurations&mdash;is entirely automated, secure, and reproducible strictly from code, eliminating manual interventions.</p>
Your responsibilities as the DevOps Engineer include:<ul><li>
Maintaining and governing all AWA Azure infrastructure utilizing Terraform or Bicep, covering multi-namespace AKS clusters, ADLS Gen2 accounts with WORM policies, API Management configurations, private endpoints, and Key Vault instances.</li><li>
Designing and optimising automated Azure DevOps pipelines managing the full lifecycle from container compilation, ACR pushing, and Notary v2 image signing, through to managed infrastructure deployments and validation testing gates.</li><li>
Managing multi-namespace AKS clusters, enforcing strict network policies, pod isolation, workload identities, and KEDA autoscaling rules based on active message queues or consumer lag.</li><li>
Overseeing container registries, enforce mandatory image signing, monitor vulnerability tracking outputs, and maintain admission control validation policies via OPA Gatekeeper.</li><li>
Administering access architectures, managed identity configurations, automated TLS certificate lifecycles, and cryptographic secret rotation schedules within Azure Key Vault.</li><li>
Constructing complex KQL queries and alerting conditions within Azure Monitor and Log Analytics to track service-level SLA breaches, runtime failures, and token utilization thresholds.</li><li>
Implementing platform security configurations, managing private connectivity endpoints, Azure Policy enforcement rules, and enterprise firewall architectures.</li><li>
Defining, implementing, and validating automated disaster recovery failover paths, maintaining target Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) for storage accounts and model serving endpoints.</li></ul><br>
<b>
Requirements</b><p><br>
We need you to have:</p><ul><li>
A deep competence in building enterprise-grade, production-ready cloud architectures using infrastructure-as-code platforms (Terraform or Bicep).</li><li>
Technical mastery over Kubernetes (AKS) configuration, including Helm/Kustomize deployment engines, network policies, and cluster admission controls.</li><li>
Practical ability to implement automated horizontal scaling strategies using Kubernetes Event-Driven Autoscaling (KEDA) or equivalent streaming metrics.</li><li>
The capability to manage multi-stage, gated deployment pipelines across multi-environment setups using Azure DevOps or GitHub Actions.</li><li>
A solid understanding of enterprise network routing, including hub-and-spoke VNets, private link endpoints, network security groups, and cloud firewall boundaries.</li><li>
A minimum of 5 years of experience in dedicated DevOps, SRE, or Platform Engineering roles, with at least 2 years explicitly focused on Azure ecosystems.</li><li>
A documented history managing production Kubernetes deployments, implementing automated RBAC, policy layers, and namespace segmentation.</li><li>
Experience writing advanced KQL (Kusto Query Language) expressions to parse logs and feed operational dashboards.</li><li>
Hold a Bachelor's degree in Computer Science, Systems Engineering, or a related technical discipline.</li></ul><p></p><p>
It would also be great if you:</p><p></p><ul><li>
Are proficient with Kubernetes Workload Identity, managed identity architectures, and Azure Key Vault access security profiles.</li><li>
Are familiar with Azure AI Foundry and API Management platforms, specifically controlling token consumption quotas, routing, and rate limits.</li><li>
Are familiar with Azure Event Hubs or Kafka consumer groups, alongside immutable ADLS Gen2 storage structure management.</li><li>
Hold an active Azure Administrator Associate (AZ-104), Azure DevOps Engineer Expert (AZ-400), or Certified Kubernetes Administrator (CKA) designations.</li></ul><br>
<b>
Benefits</b><p><b><br>
The benefits you'll enjoy as part of this role include:</b></p><br>
<ul><li>
Competitive salary
</li><li>Comprehensive personal health insurance
</li><li>Visa Sponsorship for the successful individual</li><li>
Professional development and certification support</li><li>
Subscription reimbursement relating to your role</li><li>
Opportunity to work on cutting-edge AI projects</li><li>
Monthly Employee Incentive program</li><li>
Career advancement opportunities in a rapidly growing AI company</li></ul><p><i><br>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.</i><br>
<br>
<i>At DeepLight AI, we recognise that diversity drives innovation. We are committed to fostering an inclusive environment where individuals with different thinking styles can thrive and contribute their unique strengths to our specialised AI and data solutions.</i></p><p><i>
Our goal is to ensure our application and interview process is accessible, predictable, and fair for all candidates.</i></p><p><i>
If you require any specific adjustments to the application process, or if you require any reasonable adjustments should you be successful in being processed to the interview stage, please do let us know. This information will be kept strictly confidential and will not impact hiring decisions.</i></p></div>

DevOps Engineer

MVP Application and game design L.L.C

<p>We are looking for an <b>Agentic AI Developer</b> who can design, build, and optimize advanced AI systems that go beyond simple chatbot or basic RAG implementations. The ideal candidate should have hands-on experience creating <b>multi-agent workflows, tool-using AI agents, retrieval systems, reasoning pipelines, orchestration layers, and production-ready AI architectures</b>.</p><p>This role requires someone who understands how to build complex AI systems where multiple components work together, including LLMs, vector databases, APIs, memory, tools, workflows, permissions, guardrails, and backend services. The candidate should be able to think architecturally, break down business problems into AI workflows, and design systems that are scalable, secure, reliable, and suitable for enterprise or government environments.</p><p>The candidate should also have basic to intermediate knowledge of <b>Node.js</b>, enough to connect AI services with backend APIs, build lightweight services, integrate third-party tools, and support implementation with the engineering team.</p><p><b>Technical Requirements</b></p><p>The candidate should have hands-on experience with:</p><ul><li><b>Agentic AI frameworks</b> such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or custom orchestration layers</li><li><b>Agent loops</b>, planning/execution flows, task decomposition, reflection, validation, and human-in-the-loop workflows</li><li><b>Tool calling / function calling</b>, structured outputs, JSON schemas, API execution, and tool safety controls</li><li><b>Stateful AI workflows</b>, including state machines, graph-based orchestration, session state, and workflow persistence</li><li><b>Advanced RAG pipelines</b>, including:</li><li>Chunking strategies</li><li>Embedding model selection</li><li>Hybrid search</li><li>Metadata filtering</li><li>Query rewriting</li><li>Reranking</li><li>Context compression</li><li>Retrieval evaluation</li><li>Hallucination mitigation</li><li><b>Memory architecture</b>, including:</li><li>Short-term memory</li><li>Long-term memory</li><li>User-specific memory</li><li>Vector memory</li><li>Persistent knowledge stores</li><li><b>LLM guardrails</b>, including:</li><li>Prompt injection protection</li><li>Permission-aware retrieval</li><li>Output validation</li><li>Policy checks</li><li>Tool execution safety</li><li>Response verification</li><li><b>LLM observability and evaluation</b>, including:</li><li>Tracing</li><li>Prompt/version management</li><li>Eval datasets</li><li>Regression testing</li><li>Latency analysis</li><li>Cost monitoring</li><li>Failure analysis</li><li><b>Enterprise integrations</b>, including REST APIs, databases, CRMs/ERPs, document stores, webhooks, queues, and workflow engines</li><li><b>Vector databases</b> such as Qdrant, Weaviate, Pinecone, Milvus, Chroma, pgvector, Elasticsearch, or OpenSearch</li><li><b>Secure deployment architectures</b> for private cloud, on-premise, offline, or government-secure environments</li><li><b>Node.js basics</b>, including API development, async workflows, service integration, and connecting AI systems to backend applications</li></ul><p><b>Important Note</b></p><p>This role is <b>not for someone who has only built a basic chatbot or RAG over a few PDFs</b>.</p><p>We are looking for someone who can architect real <b>agentic AI systems</b> with:</p><ul><li>Agents</li><li>Tools</li><li>Memory</li><li>Retrieval</li><li>Validation</li><li>Orchestration</li><li>Security</li><li>Monitoring</li><li>Production deployment</li></ul><p>Work location:</p><p>Abu Dhabi - in office</p><p>Job Type: Full-time</p><p>Pay: AED10,000.00 - AED11,000.00 per month</p><p>Application Question(s):</p><ul><li>What is the difference between a basic RAG chatbot and an agentic AI system?</li><li>⁠How would you handle user permissions when the agent retrieves documents from multiple departments?</li><li>How would you evaluate and audit an agent&rsquo;s decisions, tool calls, and retrieved sources in production?</li></ul><p>Experience:</p><ul><li>AI Agent &amp; Routing Engineer: 2 years (Required)</li></ul><p>Language:</p><ul><li>English (Required)</li></ul><p>Work Location: In person</p>

AI Systems Architect & Developer

Octo Outsourcing

<p>AWS Native Full-Stack / AI Platform Developer</p><p><b>Location:</b> Pakistan / Remote<br/><b>Employment Type:</b> Full-time<br/><b>Company:</b> Octo Apps / OctoApps.ai<br/><b>Department:</b> Cloud, AI Engineering, DevOps &amp; Platform Operations<br/><b>Reports To:</b> Chief Architect / Principal AI Developer</p><p>About the Role</p><p>We are looking for a strong <b>all-rounder AWS Native Developer</b> who can take full ownership of development, testing, security, deployment, troubleshooting, and platform operations for the <b>Octo Apps platform on AWS</b>.</p><p>This role is not limited to coding only. The ideal candidate must understand how application development, AWS infrastructure, DevOps, testing, monitoring, security, APIs, and AI features work together to deliver a stable, scalable, and production-ready platform. The candidate will be responsible for helping us complete, stabilize, secure, and operate Octo Apps with a target of <b>99.99% availability</b>.</p><p>You will work directly with the Chief Architect to build and manage <b>Octo Apps AI</b>, including AI-powered developer productivity tools, automation workflows, RAG-based knowledge systems, phone-system integrations, messaging APIs, and cloud-native application services.</p><p>Key Responsibilities</p><ul><li>Take end-to-end ownership of assigned Octo Apps modules, including development, testing, deployment, monitoring, troubleshooting, and support.</li><li>Develop, improve, and stabilize AWS-native applications, backend services, APIs, automation workflows, and AI-powered features.</li><li>Manage AWS infrastructure and cloud services such as <b>Lambda, API Gateway, S3, CloudFront, ECS/Fargate, EC2, RDS, DynamoDB, IAM, CloudWatch, Route 53, Secrets Manager, Bedrock, and related services</b>.</li><li>Ensure platform reliability, uptime, performance, scalability, and production readiness with a target of <b>99.99% availability</b>.</li><li>Build and maintain monitoring, alerting, logging, backup, recovery, and incident-response processes.</li><li>Perform application testing, integration testing, API testing, regression testing, security testing, and production validation before releases.</li><li>Identify, troubleshoot, and resolve issues across application code, APIs, database, AWS infrastructure, IAM permissions, environment variables, DNS, SSL, networking, and deployment pipelines.</li><li>Implement security best practices, including IAM least privilege, secrets management, secure API authentication, encrypted storage, secure deployments, and access control.</li><li>Work on AI application features such as prompt workflows, RAG pipelines, vector search, document ingestion, AI agents, automation tools, and AI API integrations.</li><li>Integrate third-party APIs including <b>Meta, WhatsApp, Messenger, Telnyx, Twilio, SendGrid, Stripe, AI APIs, CRM tools, and other business systems</b>.</li><li>Build and maintain CI/CD pipelines using GitHub Actions or similar tools.</li><li>Document architecture, deployment steps, troubleshooting guides, test cases, release procedures, and operational runbooks.</li><li>Proactively recommend improvements for performance, security, reliability, automation, and cost optimization.</li><li>Provide regular status updates, identify risks early, and take ownership until issues are fully resolved.</li></ul><p>Required Skills</p><ul><li>Strong hands-on experience with <b>AWS cloud services</b> and cloud-native application development.</li><li>Good understanding of <b>infrastructure, networking, IAM, serverless, containers, APIs, monitoring, logging, and cloud security</b>.</li><li>Backend development experience using <b>Node.js, Python, FastAPI, Express.js, NestJS, or similar technologies</b>.</li><li>Frontend understanding with <b>React, Next.js, or modern web application frameworks</b>.</li><li>Experience building, consuming, securing, and debugging <b>REST APIs</b>.</li><li>Experience with databases such as <b>PostgreSQL, MySQL, MongoDB, DynamoDB, or RDS</b>.</li><li>Understanding of <b>AI APIs</b>, including OpenAI, Claude, AWS Bedrock, or similar platforms.</li><li>Familiarity with <b>RAG, embeddings, vector databases, prompt engineering, AI workflows, or AI agents</b>.</li><li>Experience with <b>Git, GitHub, CI/CD, environment management, and production deployments</b>.</li><li>Strong testing mindset, including unit testing, integration testing, API testing, regression testing, and release validation.</li><li>Strong security mindset, including authentication, authorization, secrets handling, secure APIs, and access control.</li><li>Ability to debug independently and take ownership of issues until resolution.</li></ul><p>Preferred Skills</p><ul><li>Experience with <b>AWS Bedrock, SageMaker, Lambda, ECS/Fargate, DynamoDB, RDS, S3, CloudFront, CloudWatch, Route 53, and Secrets Manager</b>.</li><li>Experience with vector databases such as <b>Pinecone, Weaviate, Chroma, OpenSearch, pgvector, or similar</b>.</li><li>Experience with <b>Docker, Terraform, CloudFormation, AWS CDK, or infrastructure-as-code</b>.</li><li>Experience with authentication systems such as <b>OAuth, JWT, Cognito, Clerk, Auth0, or custom auth systems</b>.</li><li>Experience integrating communication APIs such as <b>Meta, WhatsApp, Messenger, Telnyx, Twilio, SendGrid, or similar</b>.</li><li>Experience supporting production SaaS platforms, multi-tenant applications, developer tools, contact-center systems, or workflow automation products.</li><li>Basic knowledge of disaster recovery, high availability, load balancing, failover, backup strategy, and incident management.</li><li>AWS certification is a plus but not mandatory.</li></ul><p>Ideal Candidate Profile</p><p>We need someone who can operate like a <b>developer, DevOps engineer, tester, security-minded engineer, and production support owner</b>. The ideal person should not wait for step-by-step instructions. They should be able to investigate problems, review logs, test fixes, improve architecture, secure the platform, document solutions, and make sure the system remains stable and available.</p><p>This person must be comfortable working in a fast-moving startup environment where ownership, accountability, and problem-solving are more important than narrow job boundaries.</p><p>Key Projects You May Work On</p><ul><li>Octo Apps AI developer productivity platform.</li><li>AI-powered automation and workflow tools.</li><li>RAG-based document and knowledge retrieval systems.</li><li>Phone system and messaging integrations with WhatsApp, Messenger, Telnyx, Twilio, and other APIs.</li><li>AWS-native backend services, APIs, infrastructure, and deployment automation.</li><li>Security, monitoring, logging, testing, backup, and high-availability improvements.</li><li>Internal admin dashboards, API routing, AI workflow orchestration, and production support tools.</li></ul><p>Qualifications</p><ul><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, IT, or equivalent practical experience.</li><li>4+ years of software development, cloud engineering, DevOps, or platform engineering experience.</li><li>2+ years of hands-on AWS experience preferred.</li><li>Experience with AI application development, AI APIs, or automation platforms preferred.</li><li>Strong communication, ownership, documentation, and troubleshooting skills.</li></ul><p>Compensation</p><p>Market-competitive salary based on experience, ownership level, and technical capability. Performance-based growth opportunities may be available as the platform scales.</p><p>How to Apply</p><p>Please send your resume, GitHub/profile links, AWS project experience, production support experience, and examples of any AI/API/cloud projects you have worked on.</p><p>Pay: Rs175,000.00 - Rs250,000.00 per month</p><p>Work Location: Remote</p>

AWS Full Stack Developer

Campbell's

<div><p><b>Since 1869, we've connected people through food they love. We&rsquo;re proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell&rsquo;s brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao&rsquo;s Homemade, Snack Factory, Snyder&rsquo;s of Hanover. Swanson, and V8.
</b></p><p></p><p><b>Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.
</b></p><p></p><p><b>Operational Support Data Engineer &ndash; Agentic AI &amp; ML Ops (Co-op)
</b></p><ul><li>We are seeking a motivated and curious Data Engineer &ndash; Agentic AI &amp; ML Ops to join our Enterprise Data &amp; Analytics team. This co-op provides hands-on experience supporting cloud-based data platforms, AI/ML operations, Generative AI, and Agentic AI solutions.
</li></ul><ul><li>You will work with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, Python, PySpark, SQL, LLMs, and modern AI/ML frameworks in an Agile environment.
</li></ul>If you are passionate about data engineering, AI, and automation, we want to hear from you.<br>
<ul><li>
</li></ul><p></p><p><b>Key Responsibilities
</b></p><ul><li>Build Data &amp; AI Pipelines: Develop and support ETL/ELT pipelines and AI/ML workflows.
</li></ul><ul><li>Data Integration &amp; Transformation: Ingest, transform, and orchestrate data using Python, PySpark, and SQL.
</li></ul><ul><li>Develop Agentic AI Solutions: Build and test AI agents and intelligent workflows for automation and data access.
</li></ul><ul><li>LLM &amp; Prompt Engineering: Design and optimize prompts and workflows using LLMs and GenAI frameworks.
</li></ul><ul><li>AI/ML Development &amp; Automation: Build Python-based scripts, APIs, and notebooks on cloud platforms.
</li></ul><ul><li>Support Analytics &amp; AI/ML: Prepare datasets for reporting, ML models, forecasting, and advanced analytics.
</li></ul><ul><li>Monitor &amp; Support Operations: Troubleshoot pipeline failures, performance issues, and data quality gaps.
</li></ul><ul><li>MLOps &amp; CI/CD: Support deployment, testing, and automation for data and AI solutions.
</li></ul><ul><li>Data Modeling &amp; Semantic Layers: Assist with STTM, data modeling, and reporting datasets.
</li></ul><ul><li>Agile Collaboration: Participate in sprint planning, stand-ups, and retrospectives.
</li></ul>Documentation &amp; Automation: Create runbooks, workflows, and technical documentation.<br>
<ul><li>
</li></ul><p></p><p><b>Learning &amp; Development Opportunities
</b></p><ul><li>Hands-on experience with Databricks, Snowflake, Azure, ADLS, ADF, and Power BI.
</li></ul><ul><li>Exposure to MLOps, GenAI, Agentic AI, LLMs, CI/CD, and automation.
</li></ul><ul><li>Experience working with AI agents, prompt engineering, and workflow orchestration.
</li></ul><ul><li>Mentorship from Data, AI/ML, and Platform Engineers.
</li></ul>Experience in Agile/Scrum and DevOps/MLOps environments.<br>
<ul><li>
</li></ul><p></p><p><b>Qualifications
</b></p><ul><li>Pursuing a degree in Computer Science, Data Engineering, Data Science, AI/ML, or related field.
</li></ul><ul><li>Knowledge of SQL, Python/PySpark, ETL/ELT, and APIs.
</li></ul><ul><li>Familiarity with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, or Git is a plus.
</li></ul><ul><li>Exposure to LLMs, GenAI, Agentic AI, MLOps, or CI/CD is beneficial.
</li></ul><ul><li>Experience with Python-based AI/ML projects or notebooks is a plus.
</li></ul><ul><li>Strong analytical and problem-solving skills.
</li></ul><ul><li>Strong communication and teamwork skills.
</li></ul><p></p><p>The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.</p></div>

Data Engineer – Agentic AI & ML Ops (Co-op)

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