generative ai engineer

Sbt Global

<div>Company Description 
On-Site
1yr contract
$10950/month 
Job Description 
About the Role
We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure.
You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. 
Job Description:<ul><li>
Design and develop algorithms for generative models using deep learning techniques</li><li>
Design and build LLM-powered applications for internal and/or customer-facing use cases</li><li>
Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems</li><li>
Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration</li><li>
Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate</li><li>
Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability</li><li>
Implement prompt engineering, structured outputs, tool calling, and model optimization strategies</li><li>
Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices</li><li>
Build monitoring, observability, and feedback loops for model and application performance in production</li><li>
Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems</li><li>
Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities</li><li>
Mentor other engineers and contribute to architecture, technical direction, and engineering best practices</li></ul> 
Qualifications 
Required Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, Machine Learning, or a related field</li><li>
5+ years of software engineering, machine/deep learning engineering, or applied AI experience</li><li>
2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production</li><li>
Strong programming skills in Python and experience with backend/API development</li><li>
Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design</li><li>
Experience in optimizing RAG pipelines using both structured and unstructured data</li><li>
Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent</li><li>
Experience in generative AI techniques such as GANs, and VAEs</li><li>
Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search</li><li>
Experience with cloud platforms such as AWS, GCP, or Azure</li><li>
Experience with Docker, Kubernetes, CI/CD, and production deployment practices</li><li>
Strong understanding of software architecture, scalability, reliability, and distributed systems</li><li>
Experience building evaluation, testing, and monitoring for AI systems</li><li>
Strong communication skills and ability to work closely with technical and non-technical stakeholder</li></ul> 
Preferred Qualifications<ul><li>
Experience fine-tuning or adapting open-source LLMs</li><li>
Advanced knowledge of natural language processing for text generation tasks</li><li>
Experience with PyTorch, TensorFlow, JAX, or related ML frameworks</li><li>
Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar</li><li>
Experience building multi-agent systems or advanced orchestration workflows</li><li>
Experience with AI safety, guardrails, red-teaming, privacy, and governance</li><li>
Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems</li><li>
Experience in customer-facing or enterprise SaaS products</li><li>
Experience in semiconductor/manufacturing, retail and e-commerce sectors</li></ul> 

Additional Information 
All your information will be kept confidential according to EEO guidelines.</div>

Senior Generative AI Engineer

Openkyber

<div>Job Title: Senior Generative AI Engineer Location: Ridgefield Park, NJ- Onsite 3 days a week Duration: Fulltime JOB SUMMARY Senior Generative AI Engineer About the Role We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure. You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. What You ll Do Design and develop algorithms for generative models using deep learning techniques Design and build LLM-powered applications for internal and/or customer-facing use cases Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock , and open-source models where appropriate Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability Implement prompt engineering , structured outputs, tool calling, and model optimization strategies Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices Build monitoring, observability, and feedback loops for model and application performance in production Establish and maintain guardrails , responsible AI practices, and security controls for enterprise AI systems Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities Mentor other engineers and contribute to architecture, technical direction, and engineering best practices Required Qualifications Bachelor s degree in Computer Science, Engineering, Machine Learning, or a related field 5+ years of software engineering, machine/deep learning engineering, or applied AI experience 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production Strong programming skills in Python and experience with backend/API development Experience with LLM application development , including prompt engineering, RAG, tool use, and structured output design Experience in optimizing RAG pipelines using both structured and unstructured data Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel , or equivalent Experience in generative AI techniques such as GANs, and VAEs Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure Experience with Docker, Kubernetes, CI/CD , and production deployment practices Strong understanding of software architecture, scalability, reliability, and distributed systems Experience building evaluation, testing, and monitoring for AI systems Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications Experience fine-tuning or adapting open-source LLMs Advanced knowledge of natural language processing for text generation tasks Experience with PyTorch, TensorFlow, JAX , or related ML frameworks Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar Experience building multi-agent systems or advanced orchestration workflows Experience with AI safety, guardrails, red-teaming, privacy, and governance Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems Experience in customer-facing or enterprise SaaS products Experience in semiconductor/manufacturing, retail and e-commerce sectors What Success Looks Like Deliver production-ready GenAI features that improve user experience and business outcomes Build reliable and scalable AI systems with strong quality, latency, and cost performance Establish best practices for evaluation, observability, and responsible AI development Help define the company s long-term Generative AI architecture and roadmap Regards, OpenKyber. | One Corporate Place South | Piscataway, NJ 08854 Tel: | Mobile: | Fax: | US| Brazil | Canada| Germany | India
For applications and inquiries, contact: hirings@openkyber.com</div>

AI-Driven OSINT Analyst

<div>Job Summary: Senior Generative AI Engineer
About the Role: We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure. You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value.
What You ll Do:
<ul><li>Design and develop algorithms for generative models using deep learning techniques</li>
<li>Design and build LLM-powered applications for internal and/or customer-facing use cases</li>
<li>Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems</li>
<li>Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration</li>
<li>Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate</li>
<li>Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability</li>
<li>Implement prompt engineering, structured outputs, tool calling, and model optimization strategies</li>
<li>Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices</li>
<li>Build monitoring, observability, and feedback loops for model and application performance in production</li>
<li>Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems</li>
<li>Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities</li>
<li>Mentor other engineers and contribute to architecture, technical direction, and engineering best practices</li>
</ul>Required Qualifications: Bachelor s degree in Computer Science, Engineering, Machine Learning, or a related field 5+ years of software engineering, machine/deep learning engineering, or applied AI experience 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production Strong programming skills in Python and experience with backend/API development Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design Experience in optimizing RAG pipelines using both structured and unstructured data Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent Experience in generative AI techniques such as GANs, and VAEs Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure Experience with Docker, Kubernetes, CI/CD, and production deployment practices Strong understanding of software architecture, scalability, reliability, and distributed systems Experience building evaluation, testing, and monitoring for AI systems Strong communication skills and ability to work closely with technical and non-technical stakeholder
Preferred Qualifications: Experience fine-tuning or adapting open-source LLMs Advanced knowledge of natural language processing for text generation tasks Experience with PyTorch, TensorFlow, JAX, or related ML frameworks Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar Experience building multi-agent systems or advanced orchestration workflows Experience with AI safety, guardrails, red-teaming, privacy, and governance Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems Experience in customer-facing or enterprise SaaS products Experience in semiconductor/manufacturing, retail and e-commerce sectors
What Success Looks Like: Deliver production-ready GenAI features that improve user experience and business outcomes Build reliable and scalable AI systems with strong quality, latency, and cost performance Establish best practices for evaluation, observability, and responsible AI development Help define the company s long-term Generative AI architecture and roadmap Compensation &amp; Benefits: Opportunity to shape the company s GenAI strategy and core platform Work on high-impact, real-world AI products with ownership from design to deployment Collaborative environment with strong technical autonomy and room for growth
For applications and inquiries, contact: hirings@openkyber.com</div>

Lead Kubernetes Architect

Realign

<div>Tampa, Florida 33592 Posted March 12th, 2026
 <div></div>Looking for more job opportunities? Click here!</div>
 <div>Job Type: Full Time
Job Category: IT
Job Description
<div>Job Title: Gen AI Engineer 
Location &ndash; Irving, TX / Tampa, FL / Edison, NJ 
FTE Only</div><div></div><div> 
Job Description</div><div>
Must Have Technical/Functional Skills</div><ul><li>Strong hands-on Python knowledge</li><li>Hands-on experience in developing API Development in Python using FastAPI/ Flask framework</li><li>Working experience in Data Processing, AI enabled workflows using python</li><li>Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI.</li><li>Basic knowledge of Hybrid prompting technique</li><li>Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.</li></ul><div></div><div> 
Good to have:</div><ul><li>Working experience with Gemini LLM</li><li>Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras</li><li>Hands-On knowledge on NLP</li><li>Understanding of model deployment and containerization (Docker).</li><li>Understanding of version control systems (Git).</li><li>Awareness of AI compliance, data privacy, and responsible AI principles</li></ul><div> 
Roles &amp; Responsibilities</div><ul><li>AI workflow development</li><li>Prompt engineering</li><li>Deployment and maintenance of AI models across all environments including Production.</li><li>Code review, testing and documentation</li><li>Continuous learning in Generative AI related fields</li></ul>
Required Skills
DEVOPS ENGINEER SENIOR EMAIL SECURITY ENGINEER</div>

Gen AI Engineer-7

<div>Irving, Texas 75014 Posted March 12th, 2026
 <div></div>Looking for more job opportunities? Click here!</div>
 <div>Job Type: Full Time
Job Category: IT
Job Description
<div>Job Title: Gen AI Engineer 
Location &ndash; Irving, TX / Tampa, FL / Edison, NJ 
FTE Only</div><div></div><div> 
Job Description</div><div>
Must Have Technical/Functional Skills</div><ul><li>Strong hands-on Python knowledge</li><li>Hands-on experience in developing API Development in Python using FastAPI/ Flask framework</li><li>Working experience in Data Processing, AI enabled workflows using python</li><li>Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI.</li><li>Basic knowledge of Hybrid prompting technique</li><li>Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.</li></ul><div></div><div> 
Good to have:</div><ul><li>Working experience with Gemini LLM</li><li>Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras</li><li>Hands-On knowledge on NLP</li><li>Understanding of model deployment and containerization (Docker).</li><li>Understanding of version control systems (Git).</li><li>Awareness of AI compliance, data privacy, and responsible AI principles</li></ul><div> 
Roles &amp; Responsibilities</div><ul><li>AI workflow development</li><li>Prompt engineering</li><li>Deployment and maintenance of AI models across all environments including Production.</li><li>Code review, testing and documentation</li><li>Continuous learning in Generative AI related fields</li></ul>
Required Skills
DEVOPS ENGINEER SENIOR EMAIL SECURITY ENGINEER</div>

Try Soft Ai

Try Soft AI is looking for a highly skilled AI Engineer with strong experience in AI Automation and Generative AI technologies to join our growing engineering team. The ideal candidate will have hands-on experience building AI-powered automation systems, AI agents, and voice AI solutions.Location: DHA Phase 2, Islamabad, Pakistan Job Type: Full-Time (Onsite) Working Hours: 08:00 PM &ndash; 05:00 AM (Pakistan Standard Time) Department: Artificial Intelligence / Automation EngineeringAbout the RoleWe are looking for a highly skilled AI Engineer with strong experience in AI Automation, LLM integrations, and workflow automation. The ideal candidate will design, develop, and deploy intelligent systems that automate business processes using AI models, APIs, and automation platforms.This role requires deep expertise in Generative AI, AI agents, API integrations, and automation pipelines. The engineer will work closely with product, engineering, and operations teams to build scalable AI-powered automation solutions for internal and client-facing applications.Key ResponsibilitiesAI Automation Development<ul><li>Design and develop AI-powered automation systems that streamline business workflows and operational processes.</li><li>Build AI agents, voice agents, and conversational assistants using LLMs and AI APIs.</li><li>Implement AI-driven automation pipelines for tasks such as lead qualification, customer support, appointment booking, and data processing.</li><li>Integrate AI models into production environments using APIs and microservices architecture.</li></ul>Generative AI &amp; LLM Implementation<ul><li>Develop applications using Large Language Models (LLMs) such as OpenAI GPT models, Claude, or similar AI platforms.</li><li>Design prompt engineering strategies to optimize LLM performance.</li><li>Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.</li><li>Build AI copilots, chatbots, and decision support systems.</li></ul>Automation &amp; Integration<ul><li>Develop advanced automation workflows using tools such as:</li><li>Make.com</li><li>Zapier</li><li>n8n</li><li>LangChain</li><li>LlamaIndex</li><li>Integrate AI systems with:</li><li>CRM platforms</li><li>Databases</li><li>SaaS products</li><li>Web applications</li><li>Third-party APIs</li></ul>Voice AI &amp; Conversational Systems<ul><li>Develop AI voice agents and voice-based automation systems.</li><li>Integrate platforms such as:</li><li>Vapi.ai</li><li>Twilio</li><li>ElevenLabs</li><li>Speech-to-Text and Text-to-Speech engines</li><li>Implement real-time conversational AI systems for customer interactions.</li></ul>Backend Development &amp; API Engineering<ul><li>Design and implement RESTful APIs and AI microservices.</li><li>Integrate AI services into web and mobile applications.</li><li>Ensure scalability, reliability, and security of AI automation systems.</li></ul>Data &amp; Model Integration<ul><li>Work with structured and unstructured data sources.</li><li>Implement vector search and embeddings using vector databases such as:</li><li>Pinecone</li><li>Weaviate</li><li>FAISS</li><li>ChromaDB</li><li>Optimize AI models for performance and cost efficiency.</li></ul>Monitoring &amp; Optimization<ul><li>Monitor AI system performance and improve model outputs.</li><li>Implement logging, error handling, and retry mechanisms for automation workflows.</li><li>Continuously optimize AI workflows for accuracy, reliability, and efficiency.</li></ul>Required Technical SkillsProgramming Languages<ul><li>Python (Highly preferred)</li><li>JavaScript / Node.js</li><li>TypeScript</li></ul>AI &amp; Machine Learning<ul><li>Generative AI</li><li>LLM Applications</li><li>Prompt Engineering</li><li>Retrieval-Augmented Generation (RAG)</li><li>AI Agents &amp; Autonomous Workflows</li></ul>AI Frameworks<ul><li>LangChain</li><li>LlamaIndex</li><li>OpenAI API</li><li>HuggingFace</li><li>Transformers</li></ul>Automation Platforms<ul><li>Make.com</li><li>Zapier</li><li>n8n</li><li>Custom automation frameworks</li></ul>Voice AI Technologies<ul><li>Vapi.ai</li><li>Twilio Voice / SMS APIs</li><li>ElevenLabs</li><li>Speech-to-Text &amp; Text-to-Speech systems</li></ul>Databases<ul><li>PostgreSQL</li><li>MongoDB</li><li>Redis</li><li>Vector Databases (Pinecone, Weaviate, FAISS, Chroma)</li></ul>Cloud Platforms<ul><li>AWS / GCP / Azure</li><li>Docker</li><li>Serverless architectures</li></ul>Other Technical Skills<ul><li>REST APIs &amp; Webhooks</li><li>OAuth &amp; API authentication</li><li>Git / Version Control</li><li>CI/CD pipelines</li></ul>Qualifications<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Software Engineering, or related field.</li><li>3+ years of experience in software development with exposure to AI technologies.</li><li>1&ndash;2+ years of hands-on experience building AI automation solutions.</li><li>Experience deploying AI-powered applications in production environments.</li><li>Excellent communication and collaboration skills. (MUST)</li></ul>Preferred Experience<ul><li>Experience building AI voice assistants or AI call agents.</li><li>Experience working with SaaS automation products.</li><li>Experience integrating AI systems with CRM platforms.</li><li>Experience in startup or fast-paced product environments.</li><li>Knowledge of AI security, privacy, and model governance.</li></ul>Soft Skills<ul><li>Strong analytical and problem-solving abilities.</li><li>Ability to design scalable automation architectures.</li><li>Excellent communication and collaboration skills. (MUST)</li><li>Ability to work independently during night shift operations.</li></ul>Work Environment<ul><li>Onsite role based in DHA Phase 2, Islamabad.</li><li>Night shift: 08:00 PM &ndash; 05:00 AM (Pakistan Standard Time).</li><li>Opportunity to work on cutting-edge AI automation and voice AI technologies.</li></ul>Work Location: In person

AI Engineer – AI Automation (Night Shift)

BigBear.ai

<div>Overview:

AskSage (BigBear.ai company) is seeking a Senior AI Engineer. This critical role involves designing, developing, and maintaining Generative AI Agents, MCP Servers, multi-agent orchestration workflows, and AI-powered tooling using Python and the Ask Sage platform. The ideal candidate will have strong prompt engineering skills, a deep understanding of Generative AI stacks such as OpenAI, Anthropic, MCP, Function tooling, etc., and a robust security background to ensure code is secure by default. Deep Experience with Generative AI and agent orchestration frameworks is required. Our FedRAMP High and DoD IL5, IL6 and Top Secret accredited cutting-edge technology enables teams to focus on strategic initiatives while we take care of the heavy lifting. We are seeking a highly skilled and experienced Senior AI Engineer with expertise in Python, generative AI, and Agent Orchestration.
What you will do:
<ul><li>Design, develop, and maintain Generative AI Agents, MCP Servers, and function tooling using Python and related frameworks.</li><li>
Build innovative Generative AI features to help Ask Sage customers automate tasks and processes.</li><li>
Implement best practices for code quality, security, and performance optimization.</li><li>
Write clean, efficient, and maintainable code with a focus on security, data privacy, and secure-by-default patterns.
</li><li>Continuous development of custom multi-agent framework and workflows to automate complex tasks and bring complex automation.
</li><li>Stay up-to-date with the latest trends and advancements in Python development and Generative AI.
</li><li>Collaborate with cross-functional teams to integrate Generative AI solutions into existing systems.
</li><li>Conduct code reviews and provide mentorship to junior developers.</li></ul>
What you need to have:
<ul><li>Minimum of 5 years of experience with Python Software Development.</li><li>
Ability to obtain a Security Clearance</li><li>
Strong Experience building Generative AI solutions, agentic AI systems, and multi-agent workflows.
</li><li>Strong prompt &amp; context engineering skills. &middot; Experience with Microsoft Power Automate to design, build, and manage automated workflows and business processes.
</li><li>Experience in building secure code with a strong understanding of security best practices (e.g., XSS, SQL injections).
</li><li>At least 3 to 4 years of experience with flagship Generative AI provider APIs (Google VertexAI, AWS Bedrock, Microsoft Azure OpenAI) and models (OpenAI GPT, Anthropic Claude, Google Gemini).
</li><li>At least 2 years of hands-on experience developing Generative AI Agents and Agent Orchestration Frameworks (OpenClaw, Claude Code, GPT Codex, etc).</li><li>
Strong problem-solving and analytical skills.
</li><li>Ability to work independently.</li></ul>
What we'd like you to have:
<ul><li>Experience with retrieval-augmented generation (RAG), vector databases (e.g., Weaviate, Pinecone, pgvector), and embedding pipelines.
</li><li>Experience with PostgreSQL and SQLAlchemy. &middot; Experience with Docker, Kubernetes, and CI/CD pipelines.
</li><li>Experience with local LLM deployment, model fine-tuning, and Hugging Face.
</li><li>Familiarity with LLM observability, evaluation frameworks, and cost/latency optimization.</li><li>
Knowledge of government compliance frameworks (FedRAMP, NIST AI RMF, CMMC 2.0).</li></ul>
About BigBear.ai:
<div>
BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai&rsquo;s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.</div><div></div><div> 
BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.</div></div><div></div>

Senior AI Engineer

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Senior Generative AI Engineer

AI-Driven OSINT Analyst

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Gen AI Engineer-7

AI Engineer – AI Automation (Night Shift)

Senior AI Engineer