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senior sqa automation analyst

ai & data engineer

associate ai automation integration engineer

Savvital

<div>
 
 About The Role
 
 
 
 A hands-on builder role at the intersection of AI engineering, automation, and systems integration. You will research, design, and ship AI-powered solutions that reduce manual effort, improve operational efficiency, and scale internal workflows. You work across multiple live projects simultaneously.
 
 
 <ul>
 <li>
 AI Engineer &mdash; design and deploy LLM-driven pipelines, agents, and AI-integrated tools across business workflows.
 </li>
 <li>
 Automation Engineer &mdash; identify, build, and maintain automations that eliminate repetitive tasks and improve throughput.
 </li>
 <li>
 Integration Engineer &mdash; connect disparate systems, platforms, and APIs into cohesive, reliable workflows.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Be Doing
 
 
 
 
 AI Engineering &amp; LLM Integration
 
 
 
 <ul>
 <li>
 Integrate LLMs (GPT-4, Claude, Gemini, etc.) into internal tools and business workflows via API.
 </li>
 <li>
 Design and maintain prompt systems: system prompts, structured outputs, chain-of-thought pipelines.
 </li>
 <li>
 Build RAG pipelines &mdash; connect knowledge bases, spec documents, and SOPs to AI agents for accurate context retrieval.
 </li>
 <li>
 Evaluate and reduce hallucinations; implement human-in-the-loop validation where needed.
 </li>
 <li>
 Stay current on model releases, capabilities, and best practices &mdash; apply them immediately.
 
 
 </li>
 </ul>
 
 Automation &amp; Workflow Engineering
 
 
 
 <ul>
 <li>
 Map existing manual workflows; identify and prioritize automation opportunities.
 </li>
 <li>
 Build end-to-end automation pipelines for repetitive tasks: data extraction, form-filling, cross-platform data transfer.
 </li>
 <li>
 Develop browser and desktop automations using Playwright, Puppeteer, or equivalent computer-use frameworks.
 </li>
 <li>
 Create internal tools &mdash; small scripts, utilities, and micro-applications that save time and reduce errors.
 </li>
 <li>
 Maintain and iterate on existing automations as workflows evolve.
 
 
 </li>
 </ul>
 
 Systems Integration
 
 
 
 <ul>
 <li>
 Connect third-party platforms, carrier portals, and SaaS tools via APIs, webhooks, and automation middleware.
 </li>
 <li>
 Build and maintain integration workflows using n8n, Make, Zapier, or Power Automate.
 </li>
 <li>
 Architect modular, maintainable systems &mdash; clean inputs, reliable outputs, clear documentation.
 </li>
 <li>
 Troubleshoot integration failures and maintain system reliability.
 
 
 </li>
 </ul>
 
 AI Research &amp; Tool Evaluation
 
 
 
 <ul>
 <li>
 Research and benchmark emerging AI tools, agent frameworks, and automation platforms.
 </li>
 <li>
 Evaluate feasibility of new tools for real use cases; produce concise internal assessment reports.
 </li>
 <li>
 Build reusable prompt libraries, automation templates, and internal knowledge bases.
 </li>
 <li>
 Contribute to AI governance practices: output validation, bias checks, ethical use.
 
 
 </li>
 </ul>
 
 TECH STACK &amp; TOOLS
 
 
 
 <ul>
 <li>
 AI &amp; LLM Platforms
 </li>
 <ul>
 <li>
 OpenAI / GPT-4o
 </li>
 <li>
 Anthropic Claude
 </li>
 <li>
 Google Gemini
 </li>
 <li>
 Open-Source LLMs - OpenClaw
 </li>
 </ul>
 <li>
 Agent &amp; Automation Frameworks
 </li>
 <ul>
 <li>
 LangChain / LangGraph
 </li>
 <li>
 AutoGen / CrewAI
 </li>
 <li>
 n8n
 </li>
 <li>
 Make (Integromat)
 </li>
 <li>
 Zapier
 </li>
 <li>
 Power Automate
 </li>
 <li>
 Playwright
 </li>
 <li>
 Puppeteer
 </li>
 </ul>
 <li>
 Development &amp; Tooling
 </li>
 <ul>
 <li>
 Python
 </li>
 <li>
 REST APIs
 </li>
 <li>
 Git / GitHub
 </li>
 <li>
 Postman
 </li>
 <li>
 Claude Code
 </li>
 <li>
 VS Code
 </li>
 <li>
 JSON / YAML
 </li>
 <li>
 Basic JavaScript
 </li>
 </ul>
 <li>
 RAG &amp; Knowledge Systems
 </li>
 <ul>
 <li>
 Vector DBs (Pinecone / Chroma)
 </li>
 <li>
 RAG Pipelines
 </li>
 <li>
 Document Parsing
 </li>
 <li>
 Embeddings APIs
 
 </li>
 </ul>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 
 Education
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Software Engineering, Information Technology, Data Science, or Artificial Intelligence preferred.
 </li>
 <li>
 Equivalent demonstrated skills and a strong project portfolio are equally valued.
 
 
 </li>
 </ul>
 
 Core AI &amp; Technical Skills
 
 
 
 <ul>
 <li>
 Working knowledge of LLMs: context windows, token efficiency, model behavior, and limitations.
 </li>
 <li>
 Prompt engineering proficiency: zero-shot, few-shot, chain-of-thought, structured output, and agentic prompting.
 </li>
 <li>
 Experience calling AI APIs and building functional workflows around them.
 </li>
 <li>
 Python scripting for automation, API integration, and data handling.
 </li>
 <li>
 Hands-on experience with at least one automation platform (n8n, Make, Power Automate, or Zapier).
 </li>
 <li>
 Familiarity with RAG concepts, vector databases, and document-grounded AI systems.
 </li>
 <li>
 Basic understanding of AI agents, tool-use, and multi-step reasoning pipelines.
 
 
 </li>
 </ul>
 
 Advanced AI Knowledge (Good to Have)
 
 
 
 <ul>
 <li>
 Awareness of latest model releases, benchmarks, and capability shifts across major AI providers.
 </li>
 <li>
 Exposure to agentic frameworks: LangGraph, AutoGen, CrewAI, or similar.
 </li>
 <li>
 Understanding of fine-tuning concepts, embeddings, and semantic search.
 </li>
 <li>
 Experience with computer-use or browser-control agents.
 
 
 </li>
 </ul>
 
 Mindset
 
 
 
 <ul>
 <li>
 Research-first: actively follows the AI space, reads docs, tests new tools.
 </li>
 <li>
 Builder: ships working systems &mdash; not just plans them.
 </li>
 <li>
 Detail-oriented: meticulous about output quality, testing, and validation.
 </li>
 <li>
 Adaptable: comfortable with ambiguity and a fast-moving environment.
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 Minimum 1 year of experience &mdash; skills and portfolio matter most.
 </li>
 <li>
 Personal projects, freelance work, coursework, or hackathon entries involving LLMs, agents, or automation all count.
 
 
 </li>
 </ul>
 
 KEY PERFORMANCE INDICATORS
 
 
 
 <ul>
 <li>
 30&ndash;60% reduction in manual processing time on automated workflows.
 </li>
 <li>
 Fast prototype-to-deployment velocity within sprint cycles.
 </li>
 <li>
 Consistent, low-error output quality across AI pipelines.
 </li>
 <li>
 High internal adoption rate and positive team feedback on built tools.
 
 
 </li>
 </ul>
 
 WORK MODEL
 
 
 
 
 Hybrid Model:
 
 This position requires
 
 4 weeks on-site
 
 for initial onboarding and training, followed by a transition to a
 
 standard hybrid schedule
 
 .
 
 
 "We value the uniqueness and experience each individual brings to the organization."
</div>

Associate – AI Automation & Integration Engineer

aAIWISE Solutions Private Limited

Role Overview We are looking for a highly skilled and innovative AI &amp; Digital Growth Engineer to design, build, and scale our digital ecosystem. This role sits at the intersection of technology, marketing, and brand growth, with a strong focus on execution, automation, and performance. You will be responsible for creating high-converting digital experiences, implementing AI-driven systems, and driving measurable growth across web, marketing, and social platforms.Core Responsibilities Website Development &amp; Optimization<ul><li>Build and manage modern, high-performance websites and landing pages</li><li>Optimize for speed, SEO, mobile responsiveness, and conversions</li><li>Develop funnels and user journeys that maximize engagement and lead generation</li></ul>AI Integration &amp; Automation<ul><li>Implement AI tools for content creation, customer interaction, and workflows</li><li>Build automation systems for lead capture, nurturing, and client onboarding</li><li>Continuously identify and deploy new AI solutions to improve efficiency and scale</li></ul>Growth &amp; Marketing Systems<ul><li>Design and execute digital growth strategies across organic and paid channels</li><li>Create and optimize marketing funnels and conversion systems</li><li>Track, analyze, and improve KPIs across campaigns and platforms</li></ul>Brand &amp; Social Media Growth<ul><li>Strengthen brand presence across all digital touchpoints</li><li>Develop and execute social media growth strategies</li><li>Guide content direction to ensure consistency, engagement, and positioning</li></ul>Tools, Integrations &amp; Tech Stack<ul><li>Work with platforms such as Webflow, WordPress, Shopify, Framer, etc.</li><li>Manage integrations with CRMs, analytics tools, email marketing systems, and ad platforms</li><li>Recommend and implement tools that enhance performance and scalability</li></ul>Required Skills Proven experience in website building (no-code/low-code + technical understanding) Strong knowledge of digital marketing, funnels, and conversion optimization Hands-on experience with AI tools and automation platforms<ul><li>Solid understanding of branding, UX/UI, and content strategy</li><li>Ability to analyze data and translate insights into actionable improvements</li></ul>Preferred Profile<ul><li>Hybrid thinker: technical + creative</li><li>Highly proactive and execution-driven</li><li>Passionate about emerging technologies and AI trends</li><li>Strong problem-solving and communication skills</li></ul>Success Metrics<ul><li>High-performing, conversion-optimized website ecosystem</li><li>Efficient, scalable automation systems</li><li>Consistent growth in leads, engagement, and revenue</li><li>Strong and cohesive digital brand presence</li></ul>Note This is not a support role &mdash; it is a builder and growth driver position. You will play a key role in shaping the company&rsquo;s digital infrastructure, brand, and future scalability.Pay: Rs80,000.00 - Rs120,000.00 per monthWork Location: In person

AI & Digital Growth Engineer

Cloudelligent

<div>
 
 
 Position Title:
 
 Sr. AWS DevOps Engineer- Kubernetes Expertise&nbsp;
 
 
 Job Timings:
 
 8am-5pm Central Time (US)&nbsp;
 
 
 Location:
 
 &nbsp;Islamabad
 
 
 
 About Cloudelligent&nbsp;
 
 
 
 Cloudelligent is an AWS Premier Consulting Partner helping organizations modernize, migrate, and innovate in the cloud. We work at the intersection of cloud, data, and AI to solve real business problems and not just implement technology. With an international footprint, Cloudelligent is customer-obsessed and focuses on Generative AI and Agentic AI to deliver practical, scalable solutions.
 
 
 
 Job Objective&nbsp;
 
 
 
 As an experienced DevOps Engineer your primary role would be to build and deploy complex cloud environments for our customers using innovative automation tools and cutting-edge technologies. You will be responsible for setting up, maintaining, and evolving the AWS cloud architecture and supporting infrastructure monitoring and alerting, issues troubleshooting, and developing required automation for our customers.&nbsp;
 
 
 
 Responsibilities&nbsp;
 
 
 <ul>
 <li>
 
 Work alongside a team of DevOps Engineers to architect, build, and deploy AWS cloud infrastructure that is redundant, resilient, scalable, self-sustaining, and self-healing.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Promote infrastructure as code and automation as much as possible. To achieve this, you must have extensive knowledge of the DevOps tool sets like Terraform, Cloudformation, CircleCI, Gitlab, Jenkins, Docker, Kubernetes.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Design, build, and maintain our Kubernetes infrastructure, including clusters, namespaces, and deployments.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Work on projects independently with customers and stakeholders, gathering their requirements and informing them of new features and enhancements.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Create and improve current operational practices and procedures.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Ensure the implementation and maintenance of compliance and security practices in operational infrastructure.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Responsible for training and mentoring junior DevOps engineers and new team members.&nbsp;
 
 </li>
 </ul>
 
 
 Requirements&nbsp;
 
 
 <ul>
 <li>
 
 Bachelor&rsquo;s in software/computer engineering, computer science or related field.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Effective communication skills (proficiency in English language).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 5+ years of professional experience in DevOps engineering.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 4+ years of using CI/CD tools (Jenkins, CircleCI, Gitlab, or similar)&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience in Infrastructure as code (Terraform / Cloudformation/CDK) and using container orchestration tools (Kubernetes/EKS or ECS, Rancher, etc.)&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience of using configuration management tools (Puppet, Ansible, etc.) and working with containers (Docker or Docker-Compose, etc.)&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience of using Scripting when necessary (Bash, Python, Ruby, Go or Javascript, etc.)&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Self-driven, ability to work independently or as part of a project team with limited supervision.&nbsp;
 
 </li>
 </ul>
 
 
 Technical Experience/Expertise&nbsp;
 
 
 <ul>
 <li>
 
 Strong hands-on expertise with solution architecting environments in AWS cloud space.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong hands-on experience with code pipeline design, development, and managing CI/CD workflows and tools.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Comprehensive understanding and hands-on experience of core DevOps concepts (CI/CD, Agile &amp; Automation).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Extensive experience in designing, deploying, and managing Kubernetes clusters in production environments.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Expertise in containerization technologies such as Docker, including creating Docker images, managing Docker registries, and configuring Docker runtime environments.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Familiarity with monitoring and logging tools such as Prometheus, Opentelemetry, Grafana, ELK stack (Elasticsearch, Logstash, Kibana).&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Extensive knowledge and hands-on experience of IP networking, VPN's, DNS, load balancing, and firewall.&nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Extensive knowledge and hands-on experience with designing a secure infrastructure using current cloud-native security standards.&nbsp;
 
 </li>
 </ul>
 
 
 Good to have&nbsp;
 
 
 <ul>
 <li>
 
 AWS Certified Solutions Architect Associate/Professional and/or&nbsp;AWS Certified DevOps Professional &nbsp;&nbsp;
 
 </li>
 <li>
 
 Certified Kubernetes Administrator (CKA)&nbsp;
 
 </li>
 </ul>
 
 
</div>

Sr. AWS DevOps Engineer- Kubernetes Expertise

Fusemachines

<div>
 
 About Fusemachines
 
 
 
 Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients&rsquo; AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
 
 
 Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
 
 
 
 Type: Remote, Full-time
 
 
 
 Role Overview
 
 
 As an Applied AI Engineer(Automation), you will deliver high-impact AI and automation solutions for clients&mdash;owning work from requirements discovery through prototype and production deployment. You&rsquo;ll build reliable, maintainable systems that integrate LLMs into real business workflows via APIs, automation platforms, and backend services.
 
 
 This is a mid-to-senior individual contributor role. You&rsquo;ll collaborate closely with Solutions Architects, Delivery/Engagement leads, and Product Managers to scope, build, ship, and iterate on client solutions.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design &amp; Deploy: Design, develop, and deploy tailored AI and automation solutions aligned to client objectives
 </li>
 <li>
 Build Workflows &amp; Services: Translate business problems into production-grade AI workflows and services using Python, automation tools (n8n/Make/Zapier or similar), and LLM platforms/APIs (e.g., OpenAI, IBM watsonx.ai, Amazon Bedrock), plus retrieval systems
 </li>
 <li>
 Agentic Systems: Build and deploy agentic workflows using LangChain, LangGraph, and Google ADK, including tool calling and structured outputs
 </li>
 <li>
 Retrieval &amp; Knowledge Systems: Implement RAG pipelines using vector databases and search technologies (e.g., Pinecone, Elasticsearch, pgvector) and graph databases when appropriate
 </li>
 <li>
 Prototype &rarr; Production: Ship fast prototypes, then harden them into scalable systems (testing, reliability, deployment, monitoring) independently or with a team
 </li>
 <li>
 Client Partnership: Participate in discovery, run technical calls/demos when needed, and communicate tradeoffs clearly to client and internal stakeholders
 </li>
 <li>
 Ongoing Support &amp; Iteration: Improve deployed solutions through feature work, bug fixes, monitoring, prompt/model improvements, and additional automations
 </li>
 <li>
 Documentation: Produce clear technical documentation, client demos, and internal playbooks to enable reuse and scalability
 </li>
 <li>
 Continuous Learning: Stay current on LLM tooling and delivery best practices to improve quality and speed
 
 
 </li>
 </ul>
 Success in This Role Looks Like
 
 
 <ul>
 <li>
 Solutions consistently meet or exceed client expectations and show measurable impact (time saved, cost reduced, improved conversion/deflection, faster cycle time)
 </li>
 <li>
 Clients trust you as a go-to engineering partner and expand usage of deployed AI workflows
 </li>
 <li>
 Deliveries are production-ready: monitored, testable, documented, and maintainable
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 3&ndash;8 years of software or AI engineering experience (mid-to-senior)
 </li>
 <li>
 2&ndash;3+ years of AI Automation, Generative AI, or Agentic AI (mid-to-senior)
 </li>
 <li>
 Strong Python engineering skills and experience building APIs/services (e.g., FastAPI)
 </li>
 <li>
 Hands-on experience integrating LLMs (e.g., OpenAI APIs or equivalents), including prompt design, structured outputs, and basic evaluation practices
 </li>
 <li>
 Experience with at least one workflow automation platform (n8n, Make, Zapier, or similar) and building reliable integrations
 </li>
 <li>
 Familiarity with RAG fundamentals and retrieval systems (embeddings, vector search); exposure to vector databases and/or Elasticsearch
 </li>
 <li>
 Production engineering fundamentals: Docker, cloud deployment (AWS/GCP/Azure/IBM), and experience with async/queuing patterns (e.g., Celery, Redis, Kafka)
 </li>
 <li>
 Comfort operating in a client-facing environment: technical calls, demos, and collaborating with cross-functional stakeholders
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with fine-tuning LLMs or other ML models; broader ML exposure is a plus (not required)
 </li>
 <li>
 Familiarity with observability and tracing (e.g., LangSmith, OpenTelemetry) and prompt/version lifecycle management
 </li>
 <li>
 Experience with graph databases / knowledge graphs
 </li>
 <li>
 Familiarity with data governance and AI governance concepts (PII handling, auditability, access controls, risk awareness)
 </li>
 <li>
 Prior consulting experience or work in fast-paced startup environments
 
 
 </li>
 </ul>
 
 Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
 
 
 
 Powered by JazzHR
 
 
 DXag1oObkj
</div>

Applied AI Engineer (Automation)

CXAi

<div>CXAi is a digitally powered, human delivered Global Customer Experience Management organization with multiple locations in Canada and abroad. We provide a wide range of business solutions to help businesses thrive. We are sought-after solutions partner for Omni Channel CX, Digital Transformation, Consulting and Technology solutions.
Our mission is to deliver elevated customer experiences to our clients, leveraging deep operational knowledge and process expertise, a strong and versatile technology stack, and a diverse geographic footprint. We focus on engaging early with our clients and leverage a consultative approach to deeply understand our clients&rsquo; brands, and design customized solutions to complex customer challenges.
Job Description
We are seeking a forward-thinking leader to drive enterprise-wide automation through Agentic AI systems, leveraging advanced Large Language Models (LLMs), Machine Learning (ML), and platforms such as Claude.
This role will be responsible for designing, implementing, and scaling AI-driven solutions across all departments&mdash;transforming how work gets done through intelligent automation, augmentation, and decisioning.
This role sits at the core of our transformation &ndash; bringing together LLMs, ML and Agentic AI to redefine how work is done. You will enable a future where AI augments human capability, strengthens customer relationships and drives scalable growth.
The ideal candidate brings a strong combination of hands-on technical expertise in LLMs/ML, and the ability to translate AI capabilities into real business outcomes across CX, operations, and back-office functions. 
Key Responsibilities<ul><li>Define and execute the enterprise AI strategy, driving adoption of Agentic AI, LLMs, and ML aligned to business KPIs</li><li>Identify and implement high-impact use cases across predictive analytics, generative AI, and intelligent automation</li><li>Design, build, and deploy AI agents and workflows with capabilities like multi-step reasoning, tool integration, and decision-making</li><li>Lead hands-on development using LLMs (e.g., Claude), orchestration frameworks, and ML models</li><li>Drive enterprise-wide adoption of LLMs across Customer Support, Finance, HR, and Operations, including training and enablement</li><li>Develop reusable assets such as prompt libraries, templates, and AI playbooks</li><li>Integrate AI solutions with CRM, CX platforms, and data/BI systems to enable end-to-end automation</li><li>Establish governance frameworks for responsible AI, including accuracy, bias mitigation, and compliance</li><li>Monitor performance and continuously optimize AI solutions to improve efficiency, cost, and productivity</li><li>Evaluate AI technologies and lead the transition to AI-first architecture</li><li>Build and lead AI/ML teams while upskilling the broader organization</li></ul> 
Required Qualifications<ul><li>2&ndash;12+ years of experience in AI, Machine Learning, or Automation</li><li>Proven experience deploying LLMs in production and building ML models for business use cases</li><li>Experience with Agentic AI or autonomous workflow automation</li><li>Hands-on expertise with LLMs (e.g., Claude), prompt engineering, and API integration</li><li>Experience with LLM orchestration frameworks and Python-based ML ecosystems</li><li>Strong understanding of NLP, generative AI, and predictive modeling</li><li>Experience in BPO, CX, or operations-driven environments preferred</li></ul> 
Preferred Qualifications<ul><li>Experience building AI copilots or internal AI platforms</li><li>Familiarity with Azure AI / Microsoft ecosystem (Fabric, Power BI, Dynamics)</li><li>Experience in speech analytics, sentiment analysis, or behavioral modeling</li><li>Understanding of data engineering and data pipelines</li></ul></div>

Head of Agentic AI & Automation

10Pearls

<div>Company Overview
10Pearls is an end-to-end digital technology services partner helping businesses utilize technology as a competitive advantage. We help our customers digitalize their existing business, build innovative new products, and augment their existing teams with high performance team members. Our broad expertise in product management, user experience/design, cloud architecture, software development, data insights and intelligence, cyber security, emerging tech, and quality assurance ensures that we are delivering solutions that address business needs. 10Pearls is proud to have a diverse clientele including large enterprises, SMBs and high growth startups. We work with clients across industries, including healthcare/life sciences, education, energy, communications/media, financial services, and hi-tech. Our many long-term, successful partnerships are built upon trust, integrity and successful delivery and execution. 
 
Role 
We are hiring a Senior Test Engineer to lead testing strategy, quality engineering, and automation initiatives across AI, data, and platform-driven projects. In this role, you will work closely with engineering, product, and data teams to ensure high-quality, scalable, and reliable delivery across APIs, web applications, and modern architectures, including systems powered by GenAI capabilities. You will be responsible for defining end-to-end test strategies, building and optimizing automation frameworks, and integrating quality practices into CI/CD pipelines. The role also involves validating complex data workflows, ensuring performance and security standards, and driving a shift toward automation-first and quality-at-scale practices. This is an ideal opportunity for someone who thrives in fast-paced environments and is passionate about delivering robust, future-ready digital solutions. 
 
Responsibilities<ul><li>
Lead the QA Engineering function by assigning, supervising, and evaluating the performance of senior QA team members.</li><li>
Drive continuous improvement of QA practices by refining end-to-end testing strategy, execution processes, and reporting mechanisms.</li><li>
Oversee and review test estimates, test plans, test strategies, status reports, and automation initiatives while managing day-to-day resource allocation and dependencies.</li><li>
Set, monitor, and achieve annual as well as continuous improvement goals for the QA team.</li><li>
Collaborate closely with Test Architects to design and implement scalable automation strategies across multiple environments.</li><li>
Partner with Project Management, Delivery, and Engineering teams to ensure timely delivery of high-quality products.</li><li>
Analyze functional specifications and translate them into effective test designs aligned with business requirements.</li><li>
Lead the creation and review of test plans, test cases, and test scripts to ensure comprehensive test coverage.</li><li>
Define and execute quality roadmaps and strategic vision for QA across release trains.</li><li>
Establish and track measurable KPIs and metrics to monitor product quality and process improvement progress.</li><li>
Enhance the hiring process by defining evaluation criteria for QA roles and implementing best practices in technical assessments and interviews.</li><li>
Ensure accountability for the quality of all QA deliverables, workflows, and stakeholder relationships.</li><li>
Perform all core responsibilities associated with the Test Manager role, ensuring alignment with organizational quality standards.</li></ul>
Requirements<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, or related field; ISTQB or equivalent certification preferred</li><li>
Strong experience in automation frameworks and CI/CD integration with exposure to cloud, containers, and data/ML workflows</li><li>
API testing (contract validation, schema, authentication, edge cases)</li><li>
Performance testing (load, stress, spike, soak testing)</li><li>
Security validation (OWASP Top 10, JWT, headers, access controls)</li><li>
Data pipelines and ML workflow validation</li><li>
UI Automation: Playwright, Cypress, Selenium</li><li>
API Testing: Postman, REST Assured, pytest, SuperTest</li><li>
Performance Testing: k6, JMeter, Locust</li><li>
Security Tools: OWASP ZAP, Burp Suite</li><li>
CI/CD &amp; DevOps: Azure DevOps, GitHub Actions, Docker</li><li>
Programming: Python, Node.js, TypeScript</li><li>
Define and own test strategy, plans, and quality KPIs</li><li>
Design, build, and maintain automation frameworks (API, UI, integration)</li><li>
Integrate automated tests into CI/CD pipelines with reporting and quality gates</li><li>
Create and manage test data, environments, and mocks</li><li>
Perform exploratory testing alongside automation-first approaches</li><li>
Validate system performance, reliability, and basic security</li><li>
Collaborate with stakeholders and mentor junior team members</li></ul> 

n9aRJ0BGZX</div>

Staff/Sr Software Consultant - Automation

ZENCLOUD TECHNOLOGIES (PRIVATE) LIMITED

We are looking for a talented and motivated Full Stack Engineer with 1&ndash;2 years of experience to join our growing team. The ideal candidate should have strong hands-on experience in the MERN Stack (MongoDB, Express.js, React.js, Node.js) along with practical knowledge of Python and Agentic AI systems for building intelligent, scalable, and modern applications.Key Responsibilities:<ul><li>Develop and maintain full stack web applications using the MERN Stack.</li><li>Build responsive and user-friendly front-end interfaces using React.js.</li><li>Design and develop scalable back-end services and REST APIs using Node.js / Express.js.</li><li>Manage and optimize MongoDB databases.</li><li>Develop AI-powered features, workflows, and automation using Python.</li><li>Build and integrate Agentic AI solutions, LLM-based tools, AI assistants, and autonomous workflows.</li><li>Collaborate with cross-functional teams to implement innovative features.</li><li>Troubleshoot, debug, and optimize system performance.</li><li>Write clean, maintainable, and efficient code following best practices.</li></ul>Required Skills &amp; Qualifications:<ul><li>1&ndash;2 years of professional experience in Full Stack Development.</li><li>Strong hands-on experience with MongoDB, Express.js, React.js, and Node.js.</li><li>Proficiency in Python for backend development, automation, or AI solutions.</li><li>Experience with Agentic AI, AI agents, LLM integrations, or workflow automation tools.</li><li>Solid knowledge of JavaScript, HTML5, CSS3.</li><li>Experience with REST APIs and third-party integrations.</li><li>Familiarity with Git/version control systems.</li><li>Strong problem-solving and communication skills.</li></ul>Work Location: In person

Full Stack Engineer (MERN Stack + AI/Python)

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