llm engineer

Recruber

<div>Are you passionate about building next-generation AI systems that leverage Large Language Models (LLMs) to automate complex tasks and enable intelligent decision-making? Join LevelShift as a Data Scientist and design end-to-end solutions across intelligent pipelines, agentic workflows, and AI-native system modernization. 
 
What Youll Do 
 
As a Data Scientist at LevelShift, you will: 
 
<ul><li>Design &amp; Build AI Pipelines: Develop intelligent, end-to-end data pipelines using LLMs for document generation, summarization, reasoning, and automation.</li>
<li>Agentic Systems: Architect and implement autonomous workflows where AI agents interact with tools, APIs, memory, and other agents to achieve multi-step objectives.</li>
<li>LLM Engineering: Apply prompt engineering, retrieval-augmented generation (RAG), and planning techniques to enable contextual reasoning and advanced decision-making.</li>
<li>System Modernization: Analyze rule-based engines, stored procedures, and monolithic applications, and re-engineer them into modular, AI-native components that handle structured and unstructured data.</li>
<li>Model Optimization: Fine-tune foundation models or adapt them with LoRA, transfer learning, or domain-specific techniques for performance improvements.</li>
<li>Cloud &amp; Deployment: Orchestrate scalable AI services and workflows in cloud environments.</li> 
</ul> 
Your Skillset 
 
Were looking for an experienced AI/ML professional with strong expertise in LLM-powered systems. 
 
Technical Skills: 
 
<ul><li>5+ years in AI/ML solution design and development, with hands-on LLM integration.</li>
<li>Python Advanced proficiency for AI/ML development and orchestration.</li>
<li>LLM Development Prompt engineering, chaining logic, context window management, API integration.</li>
<li>Agent Frameworks Memory, planning, coordination, and decision-making in multi-agent systems.</li>
<li>RAG Vector databases, embeddings, and retrieval-augmented knowledge systems.</li>
<li>Cloud Deployment and management of AI services, preferably on Microsoft Azure.</li> 
</ul> 
Good to Have
<ul><li>Experience with PCF or React for building intelligent front-end components.</li>
<li>Contributions to open-source AI frameworks or research.</li> 
</ul> 
Certifications Preferred
<ul><li>Microsoft Certified: Azure AI Engineer Associate (AI-102) or equivalent.</li> 
</ul> 
Why LevelShift?
<ul><li>Work on cutting-edge LLM-based AI projects with global impact.</li>
<li>Collaborate with experts in AI, ML, and cloud technologies.</li>
<li>Grow your career in an innovation-driven, learning-focused environment.</li> 
</ul> 
If youre ready to design and deliver intelligent AI/ML solutions, apply now at joinus@levelshift.com and take the next step in your Data Science career!</div>

Data Scientist

Kapture CX

<div>
 
 About The Role
 
 
 
 We are looking for a
 
 Software Engineer
 
 passionate about
 
 Generative AI
 
 to join our team. You will work on building intelligent, production-grade applications using cutting-edge models like GPT, LLaMA, Claude, or open-source alternatives. This is a hybrid role that combines software engineering best practices with deep interest in AI/ML, especially
 
 LLM-based
 
 applications such as
 
 RAG, chatbots, agentic systems, and prompt engineering
 
 .
 
 
 You&rsquo;ll work alongside product managers, ML researchers, and engineers to deliver robust, scalable solutions with real-world impact.
 
 
 
 Key Responsibilities
 
 
 
 Build, deploy, and maintain
 
 LLM-powered applications
 
 using APIs or open-source models.
 
 
 Implement and optimize
 
 RAG (Retrieval-Augmented Generation)
 
 pipelines.
 
 
 Integrate and experiment with
 
 LangChain, LlamaIndex
 
 , and
 
 agentic frameworks
 
 .
 
 
 Write production-grade code and deploy services in cloud environments (AWS, GCP, Azure).
 
 
 Collaborate cross-functionally with design, ML, and backend teams.
 
 
 Stay up to date with latest in GenAI: open models, prompting strategies, fine-tuning, etc.
 
 
 
 Required Skills &amp; Qualifications
 
 
 
 2&ndash;4 years of experience in software development, preferably in Python or JavaScript/TypeScript.
 
 
 Solid understanding of
 
 data structures, algorithms, and system design
 
 .
 
 
 Experience building and deploying REST APIs or microservices.
 
 
 Familiarity with
 
 GenAI concepts
 
 &ndash; LLMs, transformers, vector embeddings.
 
 
 
 Hands-on Experience With One Or More
 
 
 
 
 LangChain / LlamaIndex
 
 
 
 
 OpenAI / Cohere / Anthropic / HuggingFace models
 
 
 
 
 Pinecone / Weaviate / FAISS / Qdrant (vector DBs)
 
 
 
 
 Nice-to-Have (Bonus Skills)
 
 
 
 Experience working on
 
 chatbots
 
 ,
 
 document Q&amp;A
 
 , or
 
 agentic workflows
 
 .
 
 
 Exposure to
 
 ML model fine-tuning
 
 or
 
 prompt optimization
 
 .
 
 
 Familiarity with
 
 Docker
 
 ,
 
 Kubernetes
 
 , or
 
 CI/CD pipelines
 
 .
 
 
 Contributions to open-source GenAI projects.
 
 
 
 What You'll Get
 
 
 
 Work on real-world, AI-first products from scratch.
 
 
 Exposure to state-of-the-art LLM tools and platforms.
 
 
 Learn from a collaborative, hands-on engineering + ML team.
 
 
 Fast-paced environment with full ownership and impact.
</div>

Software Engineer- Gen AI

Harris Silicone & Glass Pvt. Ltd.

Junior Machine Learning / AI Engineer (Computer Vision &amp; Generative AI &ndash; LLMs)Location: On-siteExperience: 6 months &ndash; 1 yearType: Full-timeAbout the RoleWe&rsquo;re looking for a passionate Junior ML/AI Engineer with foundations in Computer Vision and Generative AI using Large Language Models (LLMs).You&rsquo;ll work on real-world AI systems combining visual intelligence (face recognition, detection, tracking) with language understanding and generation (LLM-based automation, chat systems, data agents).If you&rsquo;re excited by models like GPT, LLaMA, Mistral, or Claude, and love integrating vision + language to create smart systems &mdash; this role is for you!Key Responsibilities&middot; Build and optimize computer vision pipelines (detection, tracking, face recognition, etc.) using frameworks like OpenCV, YOLO, and InsightFace&middot; Develop LLM-powered applications (chatbots, summarizers, document understanding tools, etc.)&middot; Fine-tune and prompt LLMs (OpenAI GPTs, LLaMA, Mistral, Phi, etc.) for domain-specific use cases&middot; Integrate ML and LLM models into scalable backends (FastAPI, Flask)&middot; Collaborate on multimodal AI projects combining image and text intelligence&middot; Deploy models efficiently using Docker or ONNX Runtime&middot; Experiment with open-source models from Hugging Face and LangChain, LangGraphRequired Skills &amp; Tools&middot; Core ML &amp; AI:&middot; Python, NumPy, Pandas, Scikit-learn&middot; PyTorch or TensorFlow&middot; OpenCV, Mediapipe, InsightFace, YOLOv8Generative AI / LLMs:&middot; Hugging Face Transformers&middot; OpenAI API / Ollama / LLaMA / Mistral / Phi&middot; LangChain, LangGraph, LlamaIndex, or Haystack&middot; Prompt engineering and few-shot tuning&middot; Tokenization, embeddings, and retrieval-augmented generation (RAG)&middot; Knowledge of vector databases (FAISS, Chroma, Pinecone)Development &amp; Integration:&middot; FastAPI or Flask&middot; REST APIs, JSON, async programming&middot; Docker, Git, and basic CI/CD&middot; Bonus Skills (Nice to Have):&middot; Fine-tuning LLMs with LoRA or PEFT&middot; GPU usage (CUDA, cuDNN)&middot; Familiarity with MLOps tools (Weights &amp; Biases, MLflow, DVC)Qualifications&middot; Bachelor&rsquo;s degree in Computer Science, AI, Data Science, or related field&middot; 6 months &ndash; 1 year of practical experience (internship, research, or projects)&middot; Strong understanding of ML fundamentals and interest in generative AIWhy Join Us&middot; Work on real applied AI projects in vision and language&middot; Learn directly from senior AI engineers and researchers&middot; Gain experience with state-of-the-art LLM frameworks and tools&middot; Access to GPU-powered systems, real-world data, and production pipelines&middot; A collaborative, innovative, and growth-driven cultureApply Now: https://hsxtech.odoo.com/jobs/junior-ai-developer-22Job Type: Full-timeWork Location: In person

Junior Machine Learning / AI Engineer

EPAM Systems

<div>We are seeking a Senior AI Engineer to design and develop comprehensive AI applications, including chatbots, Q&amp;A systems, and agent workflows.
This role involves staying updated with the latest LLM technologies and contributing to innovative AI projects. Join our team to advance your expertise in AI engineering and deliver impactful solutions that meet client needs.
Responsibilities<ul><li>
Design, implement, and maintain end-to-end AI applications, including chatbots, Q&amp;A platforms, and agent workflows</li><li>
Collaborate directly with clients to understand their needs, identify opportunities, and recommend LLM-driven solutions</li><li>
Develop and manage robust data pipelines, prompt strategies, and datasets to ensure effective and accurate AI models (Will be a plus)</li><li>
Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable, and compliant with industry regulations (Will be a plus)</li><li>
Conduct research and rapid prototyping to validate technical feasibility and demonstrate business value of AI solutions</li><li>
Stay current with evolving LLM technologies, frameworks, and methodologies to continuously improve solutions and client outcomes</li></ul>
Requirements<ul><li>
Strong proficiency in Python, experience with web frameworks like FastAPI or similar</li><li>
Understanding of the AI application development lifecycle</li><li>
Experience with rapid UI prototyping using Streamlit, Gradio, or similar frameworks</li><li>
Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangGraph, LlamaIndex, Strands Agents, etc.)</li><li>
Knowledge of advanced AI integration patterns (e.g., RAG, Agents)</li><li>
Experience deploying AI solutions at scale, with considerations for performance, cost-efficiency, and maintainability</li><li>
Proven ability to evaluate generative AI quality using metrics such as retrieval and classification scores, as well as LLM-based evaluation methods</li><li>
Proven experience in AI engineering and delivering ML-based solutions</li><li>
Strong problem-solving skills and attention to detail</li><li>
Excellent communication, collaboration, and interpersonal skills</li></ul>
Nice to have<ul><li>
Experience designing experiments, conducting A/B tests, and iterating on models based on user feedback</li><li>
Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms</li><li>
Familiarity with emerging protocols such as MCP, A2A, ACP, etc.</li><li>
Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)</li><li>
Experience with enterprise AI platforms such as AWS AgentCore or Databricks AgentBricks or Google Agents Space, or Azure AI Foundry</li><li>
Experience with observability and monitoring tools and frameworks</li></ul>
Technologies<ul><li>
Python, PyTorch, Hugging Face, LangChain</li><li>
Vector databases including Qdrant, FAISS, Chroma</li><li>
APIs for LLMs such as Azure OpenAI and AWS Bedrock</li></ul>
We offer<ul><li>
CONTINUOUS UPSKILLING, LEARNING &amp; DEVELOPMENT<ul><li>
Diversity of tasks and projects</li><li>
Assessment center for objective review of competency level</li><li>
Personal development plan</li><li>
Mentoring programs and leadership development</li><li>
Certification and professional development support</li><li>
Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses</li><li>
English courses taught by certified teachers</li></ul></li><li>
CORPORATE BENEFITS<ul><li>
Extra leave days</li><li>
Referral bonuses</li></ul></li><li>
COMPENSATION PACKAGE<ul><li>
Competitive compensation paid in USD</li><li>
Regular salary and performance reviews</li></ul></li><li>
MEDICAL &amp; HEALTHCARE<ul><li>
Private health insurance</li><li>
Well-being events</li></ul></li><li>
WORKING ENVIRONMENT<ul><li>
Recreation areas and kitchens</li><li>
Tea, coffee, and snacks</li><li>
Well-being events</li><li>
Sports equipment and game consoles</li><li>
IT Equipment</li><li>
Microsoft's Software Assurance Home Use Program (HUP)</li></ul></li></ul>
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.</div>

Senior AI Engineer

digital.enterprises

<div>
 
 
 BUILD THE REAL-TIME INTELLIGENCE OF ADAPT
 
 
 
 
 
 
 
 About digital.enterprises
 
 
 
 digital.enterprises is shaping the future of the energy sector. We help companies run smarter integrating people, data, and technology to create intelligent, adaptive, and human-centred operations. Based in Doha, the LNG and GTL capital of the world, we fuse deep industry expertise with cutting-edge digital thinking to transform how energy companies work, connect, and grow. If you are driven by impact, speed, and purpose not titles or bureaucracy you will fit right in.
 
 
 
 
 
 
 About ADAPT
 
 
 
 ADAPT is our flagship platform a real-time digital mesh connecting the energy sectors Maintenance, Repair &amp; Operations (MRO) ecosystem. Instead of long procurement cycles, ADAPT matches buyer demand with supplier capability instantly, using live data and AI to surface qualified options with governance, auditability, and human-in-the-loop controls.
 
 
 
 
 
 
 About the Role
 
 
 
 We are seeking an experienced AI Engineer to architect and implement the intelligent layer powering ADAPT. You will build production-grade LLM applications that disintermediate RFQs through real-time matching, provide real-time decision support, and deliver actionable insights to both buyers and suppliers. This role requires deep technical expertise in modern AI frameworks, enterprise-grade system design, and the ability to translate complex business requirements into reliable AI solutions.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 - AI Application Development
 
 
 <ul>
 <li>
 Design and deploy production LLM applications (LangChain/LangGraph) for supplier matching, requirement extraction, and automated workflow orchestration.
 </li>
 <li>
 Implement sophisticated tool/function calling to integrate LLMs with external systems (inventory databases, ERPs, communications platforms).
 </li>
 <li>
 Build robust context and memory systems for multi-turn conversations and long-running industrial processes.
 </li>
 <li>
 Develop intelligent agents for supplier evaluation, alternative proposals, and emergency response scenarios.
 </li>
 </ul>
 
 
 
 
 
 - System Architecture &amp; Optimisation
 
 
 <ul>
 <li>
 Write clean, maintainable code following established patterns and best practice.
 </li>
 <li>
 Optimise inference pipelines for latency, cost, and accuracy in high-stakes environments.
 </li>
 <li>
 Design scalable architectures for concurrent users across maintenance, procurement, and supplier teams.
 </li>
 <li>
 Implement caching, batching, and performance optimisations for enterprise-scale deployments.
 </li>
 </ul>
 
 
 
 
 
 - AI Quality &amp; Reliability
 
 
 <ul>
 <li>
 Develop comprehensive evaluation frameworks (AI evals) to measure accuracy, relevance, and business impact.
 </li>
 <li>
 Design and execute fine-tuning strategies for domain-specific models (MRO terminology, supplier capability, part specifications).
 </li>
 <li>
 Explore and implement RL-based agents for dynamic supplier analysis where beneficial.
 </li>
 <li>
 Create sophisticated prompt engineering solutions that balance specificity and flexibility.
 </li>
 </ul>
 
 
 
 
 
 - Security &amp; Compliance
 
 
 <ul>
 <li>
 Implement security best practice for sensitive procurement data, supplier information, and commercial terms.
 </li>
 <li>
 Ensure compliance with data protection regulations and industry standards (ISO, API standards, etc.).
 </li>
 <li>
 Design audit trails and logging for AI-assisted decisions in regulated environments.
 </li>
 <li>
 Build safeguards against prompt injection, data leakage, and other AI-specific vulnerabilities.
 </li>
 </ul>
 
 
 
 
 
 - Domain Integration
 
 
 <ul>
 <li>
 Collaborate with domain experts to understand oil &amp; gas MRO workflows, terminology, and critical requirements.
 </li>
 <li>
 Travel to client sites, supplier locations, and operational facilities to understand real-world constraints.
 </li>
 <li>
 Translate operational requirements into technical specifications and AI capabilities.
 </li>
 <li>
 Provide technical guidance during customer implementations and onboarding.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 
 
 
 
 
 - Experience &amp; Background
 
 
 <ul>
 <li>
 5+ years of professional software engineering experience in enterprise environments.
 </li>
 <li>
 Hands-on experience delivering working AI applications in production or advanced pilot environments.
 </li>
 <li>
 Experience working in regulated or sensitive-data settings.
 </li>
 </ul>
 
 
 
 
 
 Technical Expertise
 
 
 
 
 
 
 
 - LLM Frameworks &amp; Foundation Models
 
 
 <ul>
 <li>
 Deep expertise building complex agent workflows.
 </li>
 <li>
 Hands-on with major LLMs (OpenAI, Anthropic, open-source) including API integration and optimisation.
 </li>
 </ul>
 
 
 
 
 
 - Advanced AI Patterns
 
 
 <ul>
 <li>
 Function/tool calling and external system integration.
 </li>
 <li>
 Context-window management and retrieval strategies.
 </li>
 <li>
 Memory systems for stateful conversations and long-running processes.
 </li>
 </ul>
 
 
 
 
 
 - AI Engineering
 
 
 <ul>
 <li>
 Building evaluation frameworks and metrics for LLM applications.
 </li>
 <li>
 Fine-tuning for domain-specific use cases.
 </li>
 <li>
 Experimenting with RL-based agents where impactful.
 </li>
 <li>
 Advanced prompt engineering and optimisation.
 </li>
 </ul>
 
 
 
 
 
 - Software Engineering
 
 
 <ul>
 <li>
 Clean-code principles and&nbsp;SOLID&nbsp;design patterns.
 </li>
 <li>
 Performance optimisation and scalability.
 </li>
 <li>
 Version control (Git) and&nbsp;CI/CD&nbsp;pipelines.
 </li>
 <li>
 Testing strategies for AI systems (unit, integration, end-to-end).
 </li>
 <li>
 Security best practice, data protection, and compliance awareness.
 </li>
 </ul>
 
 
 
 
 
 - Soft Skills
 
 
 <ul>
 <li>
 Communication: explain complex AI concepts to non-technical stakeholders; write clear documentation; collaborate across teams.
 </li>
 <li>
 Travel: willingness and ability to travel to operational sites, client facilities, and partner locations.
 </li>
 <li>
 Problem-solving: strong analytical thinking; break down complex business problems into implementable AI solutions.
 </li>
 </ul>
 
 
 
 
 
 - Preferred
 
 
 <ul>
 <li>
 Domain knowledge in oil &amp; gas operations, supply chain, or industrial procurement.
 </li>
 <li>
 Experience with MRO/EAM/supply chain software.
 </li>
 <li>
 Familiarity with industry-specific standards and terminology.
 </li>
 <li>
 Background in traditional ML/data science beyond LLMs.
 </li>
 <li>
 Experience with vector databases, semantic search, and RAG architectures.
 </li>
 </ul>
 
 
 
 
 
 Why join us?
 
 
 
 At digital.enterprises, AI is a partner to people, not a replacement. This is Industry 5.0 in practice: technology amplifying human capability so energy operations become safer, more reliable, and more efficient delivering secure, affordable, cleaner energy at scale. You will join a mission-driven team led by credible industry leadership with the freedom to build technology that genuinely changes how an industry works.
 
</div>

Artificial Intelligence Engineer

PeoplePlusTech Inc.

Job Title: AI EngineerLocation: Anywhere in IndiaShift: starts between 12PM to 2PM IST (8-hour shift)Responsibilities:<ul><li>Design, build, and fine-tune AI models using Azure OpenAI, Cognitive Services, and custom LLMs.</li><li>Perform monthly and on-demand model fine-tuning based on user feedback and performance metrics.</li><li>Continuously monitor AI outputs for bias, hallucinations, and accuracy, implementing corrective workflows.</li><li>Develop, enhance, and maintain Retrieval-Augmented Generation (RAG) pipelines and vector databases.</li><li>Support integration of AI models into production with scalable APIs and workflows.</li><li>Collaborate with Data Scientists, Engineers, and Developers to ensure consistent model deployment.</li><li>Create benchmarks and automated validation systems for AI model evaluation.</li><li>Ensure compliance with Responsible AI principles, SOC2, GDPR, and data privacy frameworks.</li><li>Enhance the AI feedback loop through prompt optimization, embeddings, and output evaluation.</li><li>Leverage Azure AI services (OpenAI, AI Search, Document Intelligence, Vector DB) for model orchestration.</li></ul>Qualifications:<ul><li>Proven experience in AI/ML engineering and LLM operations (fine-tuning, embeddings, RAG).</li><li>Strong programming skills in Python, including frameworks such as PyTorch, TensorFlow, and spaCy.</li><li>Hands-on experience with Azure AI tools (OpenAI, Cognitive Search, AI Studio, Data Lake).</li><li>Knowledge of prompt engineering, orchestration frameworks, and vector database optimization.</li><li>Understanding of Responsible AI, model governance, and compliance standards.</li><li>Experience deploying and managing models in production environments using CI/CD and Azure DevOps.</li></ul>Job Type: Full-timePay: From &#8377;50,000.00 per monthBenefits:<ul><li>Work from home</li></ul>

AI Engineer (URGENT HIRING - REMOTE)

Prodapt Solutions

<div>Overview:

Join the Prodapt team in building a unified, enterprise-grade environment for developing, deploying, and scaling generative AI (GenAI) applications and agentic workflows. You will help design, develop, and optimize robust GenAI solutions that empower teams to leverage LLMs, agent frameworks, and retrieval-augmented generation (RAG) for a wide range of business and technology use cases.
Responsibilities:
<ul><li>Design, develop, and maintain GenAI applications and agentic workflows using unified LLM developer APIs and Agent Builder.</li><li>Integrate and manage foundation and tuned LLMs (e.g., Gemini, GPT, Llama, Claude) for both internal and external use cases.</li><li>Build and optimize RAG pipelines leveraging centralized vector databases and embedding stores.</li><li>Develop and deploy GenAI models and BYOA (Bring Your Own Application) solutions as Docker images on Kubernetes-based infrastructure.</li><li>Implement prompt engineering, orchestration, and evaluation workflows using workbench plugins and browser extensions.</li><li>Support and extend user interfaces (web UI, browser extension, Slack integration) for interacting with GenAI agents and tools.</li><li>Ensure robust security, compliance, and governance, including role-based access control, audit logging, and data privacy controls.</li><li>Collaborate with data scientists, ML engineers, and product teams to deliver scalable, production-grade GenAI solutions.</li><li>Participate in code reviews, architecture discussions, and continuous improvement of the GenAI platform.</li></ul>
Requirements:
<h2 class="jobSectionHeader">Required Technical Skills</h2><ul><li>
Proficiency in Python and experience with LLM/GenAI model development and integration.</li><li>
Experience with containerization (Docker) and orchestration (Kubernetes) for deploying GenAI applications.</li><li>
Familiarity with LLM APIs (AI, OpenAI, Gemini, etc.) and prompt engineering best practices.</li><li>
Hands-on experience with vector databases, RAG workflows, and embedding management.</li><li>
Experience with web UI development (React, Next.js, or similar frameworks) and API integration.</li><li>
Strong understanding of security, governance, and compliance in AI/ML environments.</li><li>
Experience with CI/CD tools and automation for GenAI workflows.</li><li>
Excellent troubleshooting, debugging, and communication skills.</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Experience with agentic frameworks (LangChain, CrewAI) and multi-agent orchestration.</li><li>
Familiarity with large-scale financial/ML platforms.</li><li>
Exposure to GenAI evaluation frameworks (LLM_EVAL, AGENT_EVAL) and monitoring tools.</li><li>
Experience with Slack bot development, browser extension integration, or desktop app development.</li><li>
Knowledge of data privacy, vulnerability scanning, and compliance automation.</li></ul></div>

Senior Technical Lead (AI/ML - GenAI)

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