agentic ai engineer

FocusKPI Inc.

<div><p>We are seeking an <b>Agentic AI Engineer</b> to support the development of a customized AI agent solution for one of our clients.<br>
<br>
We're a consulting team that helps clients design and build customized AI agent solutions. You'll work across engagements &mdash; understanding client problems, architecting the right agentic approach, and shipping working systems. This is not a research role. You'll be in the work &mdash; building agents that go live, with real clients, on real timelines.<br>
<br>
<b>Environment:</b><br>
<br>
We move fast and work across multiple client contexts. You'll need to be comfortable with ambiguity, adapt quickly across industries, and take ownership of your engagements without much hand-holding.<br>
<br>
If you thrive in structured, single-product environments with long planning cycles, this probably isn't the right fit. If you love the variety of consulting and want to build things that actually ship, let's talk.<br>
<br>
<b>Work Location:</b><b> </b>Remote position (40 hours per week)<br>
<b>Duration:</b> Full-time role<br>
<b>Pay-rate:</b> $30+/hr<br>
<br>
<b>**No C2C resumes are considered**</b><br>
<br>
<b>Responsibilities:</b></p><ul><li>
Consult with clients to understand their workflows, pain points, and where agentic AI can create real leverage</li><li>
Design and build custom AI agent solutions tailored to each client's stack, data, and constraints</li><li>
Own full delivery &mdash; from architecture and prompt design to tool integration, testing, and handoff</li><li>
Build evals and monitoring so clients can trust what's running in production</li><li>
Move across engagements &mdash; you'll context-switch between clients and industries</li></ul><p><b>
Qualifications:</b></p><ul><li>
A minimum of <b>2 years</b> of experience is required</li><li><b>
Education requirements:</b> Master's degree</li><li><b>
Mandatory skills:</b> Agentic AI, Claude, LLM</li><li>
Building production-grade agentic systems using frameworks like LangChain, LangGraph, CrewAI, AutoGen, or Claude Agent SDK</li><li>
Designing agent architectures: tool routing, memory, multi-agent coordination, retrieval pipelines</li><li>
Translating a client's messy real-world process into a structured agent design</li><li>
Communicating clearly with non-technical stakeholders &mdash; you can explain what you're building and why</li><li>
Delivering under real project constraints &mdash; timelines, client expectations, shifting requirements</li></ul><p><b>
Nice to have:</b></p><ul><li>
Experience building agents for GTM use cases &mdash; sales research, outreach automation, CRM workflows, lead enrichment, or marketing operations</li><li>
Comfort connecting agents to third-party APIs, CRMs (HubSpot, Salesforce), or communication tools</li></ul><p></p><p>
Thank you!</p><p>
FocusKPI Hiring Team</p><p>
Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California, with an East Coast office in Boston, Massachusetts.</p><p>
</p><p><b>NOTICE: </b>Please be aware of fraudulent emails regarding job postings, job offers and fake checks. FocusKPI's recruiting team will strictly reach out via @focuskpi.com email domain. If you have received fraudulent emails now or in the past, please report it to https://reportfraud.ftc.gov/ .<br>
The domain @focuskpijobs.com is fraudulent and not related to FocusKPI. Please do not not reply or communicate to anyone with @focuskpijobs.com.</p><p>
</p><p>DC4HSZaJiV</p></div>

Agentic AI Engineer

Booz Allen Hamilton

<div>Agentic AI Engineer<p><b>
The Opportunity</b><b>:</b><br>
We are looking for a highly skilled Agentic AI Engineer to join our team specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.<br>
<br>
<b>What You'll Work On:</b></p><ul><li><p>
Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.</p></li><li><p>
Develop and deploy multi-agent systems using Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols to facilitate communication, tool usage, and collaborative task solving.</p></li><li><p>
Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.</p></li><li><p>
Fine-tune SLMs for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.</p></li><li><p>
Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.</p></li></ul><p></p><p>
Join us. The world can&rsquo;t wait.</p><p></p><p><b>
You Have:</b></p><ul><li><p>
4+ years of experience in software development</p></li><li><p>
3+ years of experience as an ML engineer building production-grade ML solutions using tools such as Docker or Kubernetes, including, GenAI, LLMs, DL, RL, AI agents, agentic workflows, or complex automation frameworks</p></li><li><p>
3+ years of experience with LangChain, LangGraph, AutoGen, PydanticAI, CrewAI, or LlamaIndex</p></li><li><p>
3+ years of experience working in cloud environments, including AWS and Azure and evaluating architectural tradeoffs and designing robust service-based software applications for scalable use</p></li><li><p>
Experience with MCP for tool integration and A2A for agent-to-agent collaboration and with RAG architecture and KG, including Neo4j or NebulaGraph</p></li><li><p>
Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA, evaluating LLM performance and behavior through evaluations, and building observation layers for stakeholders, including Grafana, Langfuse, LangSmith, or Phoenix</p></li><li><p>
Knowledge of modern software design patterns, including microservice design or edge computing</p></li><li><p>
Ability to adapt in a rapidly changing environment and navigate ambiguity</p></li><li><p>
TS/SCI clearance with a polygraph</p></li><li><p>
Bachelor&rsquo;s degree</p></li></ul><p></p><p><b>
Nice If You Have:</b></p><ul><li><p>
Experience deploying agentic systems in a production environment</p></li><li><p>
Experience deploying agents on edge devices such as Android or local models</p></li><li><p>
Experience integrating coding agents such as Cursor or Windsurf into an efficient development pipeline with measured results</p></li><li><p>
Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and vLLM</p></li><li><p>
Experience engineering AI capabilities in on‑premise or multi‑classification environments</p></li><li><p>
Possession of excellent verbal and written communication skills for client engagements, client-facing project work, and business development</p></li><li><p>
Master&rsquo;s degree in a CS or AI field preferred; Doctorate degree in CS or Statistics a plus</p></li></ul><p></p><p><b>
Clearance:</b></p><p>
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with polygraph is required.</p><p></p><p><b>
Compensation</b></p><p>
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen&rsquo;s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.</p><p></p>
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual&rsquo;s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen&rsquo;s total compensation package for employees. This posting will close within 90 days from the Posting Date.<p></p><p><b>
Identity Statement</b></p><p>
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.</p><p></p><p><b>
Candidate AI Usage Policy</b></p><p>
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on <b>your </b>own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited <b>unless permission is explicitly provided</b>.
</p><p></p><p><b>Work Model</b><br>
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.</p><ul><li><p><b>
Remote</b>: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.</p></li><li><p><b>
Hybrid</b>: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.</p></li><li><p><b>
Onsite</b>: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.</p></li></ul><p></p><p><b>
Commitment to Non-Discrimination</b></p><p>
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.</p></div><p></p>

ImagineArt

<div><h1 class="jobSectionHeader"><b>Principal AI Engineer (LLM Agents &amp; Orchestration)</b></h1><p><b><br>
Role Title:</b> Principal AI Engineer (LLM Agents &amp; Orchestration) <b>Team:</b> Chatly Engineering <b>Focus:</b> Building Autonomous &quot;Super Agents&quot;</p><h2 class="jobSectionHeader"><b><br>
Who We Are</b></h2><p>
Vyro is redefining the future of digital creativity. We build cutting-edge content creation tools powered by Artificial Intelligence and Machine Learning, helping millions of creators, designers, and storytellers bring their imagination to life &mdash; effortlessly.</p><p>
With a global user base of over 5 million active creators every month, Vyro&rsquo;s 20+ AI-powered apps are transforming how people design, edit, and express themselves across images, videos, and beyond.</p><p>
From intuitive AI photo editors to next-gen video creation platforms, our products are designed to make creativity accessible, fast, and limitless.</p><p>
At Vyro, we&rsquo;re a team of innovators, builders, and dreamers &mdash; known as Vyronauts &mdash; driven by passion, purpose, and the belief that technology should inspire creativity, not complicate it.</p><h3 class="jobSectionHeader"><b>
If you&rsquo;re excited about shaping the next wave of AI-powered creativity, Vyro is the place to be.</b></h3><h3 class="jobSectionHeader"><br>
<b>
About the Role</b></h3><p>
We are looking for a deep expert in Large Language Models (LLMs) to lead the architectural development of our new &quot;Super Agent&quot; within Chatly. You will move beyond simple chat interfaces to build autonomous agents capable of complex reasoning, tool usage, and seamless integration with external workflows.</p><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><ul><li><p><b>
Agent Architecture:</b> Design and implement stateful agentic workflows (using frameworks like LangGraph or custom Python/TypeScript solutions) that can plan, execute, and self-correct.</p></li><li><p><b>
Integration Ecosystem:</b> Build the &quot;hands&quot; of the agent. Develop robust integration layers that allow the LLM to interact with our internal APIs, databases, and third-party tools reliably.</p></li><li><p><b>
Latency &amp; Reliability:</b> Optimize inference pipelines for speed (streaming, token optimization) and reliability (handling hallucinations, structured output validation).</p></li><li><p><b>
Memory Systems:</b> Architect advanced RAG (Retrieval-Augmented Generation) systems to give the Super Agent persistent memory and context awareness across sessions.</p></li><li><p><b>
Evaluation &amp; Observability:</b> Establish a rigorous testing framework for non-deterministic model outputs to ensure the agent behaves as expected in production.</p></li></ul><h3 class="jobSectionHeader"><b>
Technical Requirements</b></h3><ul><li><p><b>
Core Stack:</b> Deep proficiency in Python (or TypeScript) and the modern AI stack (LangChain, LlamaIndex, DSPy).</p></li><li><p><b>
Model Internals:</b> Strong grasp of how to leverage specific model strengths (e.g., GPT-4o for reasoning, Haiku/Flash for speed) and experience with <b>Function Calling/Tool Use</b>.</p></li><li><p><b>
Vector Search:</b> Hands-on experience with vector databases (Pinecone, Milvus, Weaviate) and embedding strategies.</p></li><li><p><b>
System Design:</b> Experience designing event-driven architectures where agents respond to triggers, not just user prompts.</p></li></ul><p><b>
Why Join Us?</b></p><ul><li><p>
Opportunity to work on innovative AI products like <b>Chatly</b> and <b>Imagine</b>, shaping the future of creativity and user interaction.</p></li><li><p>
Be part of a passionate, fast-moving team that values innovation and data-driven decisions.</p></li><li><p>
Competitive compensation and benefits.</p></li><li><p>
A culture where learning, growth, and experimenting with new ideas are deeply encouraged.</p></li></ul></div><p></p>

Texas Instruments

<p></p><div><div><div><div><div><div><div><div><div><div><div><div><b>Change the world. Love your job.</b></div><p>
Texas Instruments is transforming semiconductor manufacturing through AI. This role sits within the Smart Manufacturing Automation (SMA). organization You will design, build, and operate the agentic AI infrastructure that powers factory intelligence across TI's global fab and assembly/test operations to connect large language models to live manufacturing data systems and enabling rapid decision support at scale.</p><p><b>
What You'll Do</b></p><ul><li><div>
Architect and deliver multi-agent AI systems using the A2A (Agent-to-Agent) protocol, including orchestrator and sub-agent topologies that span multiple factory data sources.</div></li><li><div>
Build and maintain MCP (Model Context Protocol) servers in Python, containerized with Docker and deployed on VMs and Kubernetes clusters; register agents and MCP servers.</div></li><li><div>
Integrate LLM inference into factory workflows; manage LiteLLM project credentials, budgets, and routing configurations.</div></li><li><div>
Develop agent tools that query manufacturing databases (MES, FDC, APC, OEE, etc.) and expose clean interfaces for downstream AI consumption.</div></li><li><div>
Design, evolve, and influence the Agent Delivery Framework.</div></li><li><div>
Establish and document agentic software development best practices; create reusable agent templates adopted across business teams.</div></li><li><div>
Build and maintain Knowledge Graph and RAG systems (Neo4j, Vectara) to enable document and parametric data retrieval across thousands of manufacturing documents and records.</div></li><li><div>
Collaborate with multiple departments, domain architects, and factory engineers to identify high ROI agent use cases, prioritize delivery, and ensure agents meet security and authentication requirements.</div></li><li><div>
Present architecture roadmaps and live agent demos to peers and senior manufacturing leadership.</div></li><li><div>
Contribute to cross-domain AI access and guardrails governance strategy.</div></li></ul></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>QUALIFICATIONS</p>
<div><div><b>Minimum Qualifications:</b></div>
<ul>
<li><div>Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field.</div></li>
<li><div>4+ years of software engineering experience, with at least 2 years focused on AI/ML systems or LLM application development.</div></li>
<li><div>Proficiency in Python and experience containerizing applications with Docker.</div></li>
<li><div>Hands-on experience building or integrating with REST API backends and asynchronous service architectures.</div></li>
<li><div>Strong communication skills &mdash; able to translate complex AI architecture decisions for non-technical manufacturing stakeholders.</div></li></ul><br>
<p></p>
<p><b>
Preferred Qualifications:</b></p>
<ul>
<li><div>Experience with multi-agent AI frameworks, agent orchestration patterns, or the MCP (Model Context Protocol) specification.</div></li>
<li><div>Familiarity with LiteLLM, Open Web UI, or similar LLM proxy/routing platforms.</div></li>
<li><div>Experience deploying workloads on Kubernetes (K8s) or cloud-adjacent enterprise platforms.</div></li>
<li><div>Working knowledge of graph databases (Neo4j) and vector search systems (Vectara, pgvector, or equivalent).</div></li>
<li><div>Prior exposure to semiconductor or discrete manufacturing data systems (MES, FDC, SPC, SCADA, APC) is a strong plus.</div></li>
<li><div>Experience with workflow automation tools (e.g. Airflow) and CI/CD pipelines (Bitbucket, Jenkins, or equivalent).</div></li>
<li><div>Master's degree or equivalent industrial AI research experience.</div></li>
</ul></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>ABOUT US</p>
<div><div><div><b>Why TI?</b>
</div><div><ul><li>Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.</li>
<li>We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI</li>
<li>Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us.</li><br>
</ul></div><p></p><br>
<div><p><b>About Texas Instruments</b>
</p><p>Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, data center, personal electronics and communications equipment. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com.<br>
</p><p></p><br>
<div><div>Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, disability, genetic information, national origin, gender, gender identity and expression, age, sexual orientation, marital status, veteran status, or any other characteristic protected by federal, state, or local laws.<br>
</div><p></p><br>
<p>If you are interested in this position, please apply to this requisition.
</p></div></div></div></div></div></div></div></div></div></div><p></p><div><div><div><div><div><div><div>TI does not make recruiting or hiring decisions based on citizenship, immigration status or national origin. However, if TI determines that information access or export control restrictions based upon applicable laws and regulations would prohibit you from working in this position without first obtaining an export license, TI expressly reserves the right not to seek such a license for you and either offer you a different position that does not require an export license or decline to move forward with your employment.</div>
</div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>25010490</div>
</div><div><div>Job Category</div>
<div>Information Technology</div>
</div><div><div>Posting Date</div>
<div>05/08/2026, 01:26 PM</div>
</div><div><div>Degree Level</div>
<div>Bachelor's Degree</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>RFAB 300 W. Renner Road, Richardson, TX, 75080, US
</div></div></div></div><div><div>ECL/GTC Required</div>
<div>Yes</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

<div>
 <p>
  <strong>
   Job Title: Agentic AI Data Engineer
  </strong>
 </p>
 <p>
  <strong>
   Hybrid: Jersey City,NJ
  </strong>
 </p>
 <p>
  <strong>
   Job Type: FullTime
  </strong>
 </p>
 <p>
  <strong>
   Max Budget : $150K
  </strong>
 </p>
 <p>
  <strong>
   Total Experience required : 5-10 Years
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Role Overview
 </p>
 <p>
  We are seeking a highly skilled Agentic AI Data Engineer to design, build, and optimize intelligent, autonomous data systems that power next-generation AI applications. This role blends data engineering, machine learning infrastructure, and emerging agent-based AI frameworks to enable scalable, self-orchestrating pipelines and decision-making systems.
 </p>
 <p>
  You will work at the intersection of data platforms, large language models (LLMs), and cloud-native architectures&mdash;building systems that can reason, act, and adapt autonomously.
 </p>
 <p>
  ---
 </p>
 <p>
  Key Responsibilities
 </p>
 <p>
  &middot; Design and implement agentic AI systems that autonomously orchestrate data workflows and decision pipelines
 </p>
 <p>
  &middot; Build scalable data pipelines for structured and unstructured data (batch + real-time)
 </p>
 <p>
  &middot; Develop and manage LLM-powered applications using retrieval-augmented generation (RAG), tool use, and multi-agent frameworks
 </p>
 <p>
  &middot; Integrate AWS AI/ML services into production-grade architectures
 </p>
 <p>
  &middot; Develop and optimize data lakes, warehouses, and lakehouse architectures
 </p>
 <p>
  &middot; Build APIs and microservices to expose AI/ML capabilities
 </p>
 <p>
  &middot; Ensure data quality, governance, and security across pipelines
 </p>
 <p>
  &middot; Collaborate with data scientists, ML engineers, and product teams to deploy AI solutions
 </p>
 <p>
  &middot; Implement monitoring, logging, and observability for AI agents and pipelines
 </p>
 <p>
  &middot; Optimize cost and performance of cloud-based AI workloads
 </p>
 <p>
  ---
 </p>
 <p>
  Required Technical Skills
 </p>
 <p>
  Cloud &amp; AWS Ecosystem
 </p>
 <p>
  &middot; Strong experience with AWS services, including:
 </p>
 <p>
  o Amazon S3, Glue, Lambda, Step Functions
 </p>
 <p>
  o Amazon Redshift / Athena
 </p>
 <p>
  o Amazon SageMaker (training, deployment, pipelines)
 </p>
 <p>
  o Amazon Bedrock (foundation models, agents, knowledge bases)
 </p>
 <p>
  AI/ML &amp; Agentic Systems
 </p>
 <p>
  &middot; Experience with LLMs and generative AI systems
 </p>
 <p>
  &middot; Hands-on with agent frameworks (e.g., multi-agent orchestration, tool calling, planning systems)
 </p>
 <p>
  &middot; Familiarity with AgentCore / agent orchestration platforms
 </p>
 <p>
  &middot; Understanding of RAG architectures, embeddings, and vector databases
 </p>
 <p>
  &middot; Experience with model deployment, inference optimization, and prompt engineering
 </p>
 <p>
  Data Engineering
 </p>
 <p>
  &middot; Strong proficiency in Python and SQL
 </p>
 <p>
  &middot; Experience with ETL/ELT tools and frameworks
 </p>
 <p>
  &middot; Distributed data processing (Spark, PySpark, or similar)
 </p>
 <p>
  &middot; Streaming technologies (Kafka, Kinesis, or similar)
 </p>
 <p>
  &middot; Data modeling and schema design
 </p>
 <p>
  Data &amp; AI Infrastructure
 </p>
 <p>
  &middot; Experience with vector databases (e.g., Pinecone, FAISS, OpenSearch)
 </p>
 <p>
  &middot; Knowledge of data lakehouse architectures (Delta Lake, Iceberg, Hudi)
 </p>
 <p>
  &middot; Containerization (Docker) and orchestration (Kubernetes)
 </p>
 <p>
  &middot; CI/CD for ML and data pipelines
 </p>
 <p>
  ---
 </p>
 <p>
  Preferred Qualifications
 </p>
 <p>
  &middot; Experience building autonomous AI agents for enterprise use cases
 </p>
 <p>
  &middot; Knowledge of multi-agent collaboration systems and planning algorithms
 </p>
 <p>
  &middot; Familiarity with LangChain, LlamaIndex, or similar frameworks
 </p>
 <p>
  &middot; Experience with MLOps and LLMOps practices
 </p>
 <p>
  &middot; Understanding of graph-based workflows and knowledge graphs
 </p>
 <p>
  &middot; Exposure to real-time AI systems and event-driven architectures
 </p>
 <p>
  ---
 </p>
 <p>
  Soft Skills
 </p>
 <p>
  &middot; Strong problem-solving and system design skills
 </p>
 <p>
  &middot; Ability to work in fast-paced, evolving AI environments
 </p>
 <p>
  &middot; Effective communication and cross-functional collaboration
 </p>
 <p>
  &middot; Curiosity and adaptability to emerging AI technologies
 </p>
 <p>
  ---
 </p>
 <p>
  Education &amp; Experience
 </p>
 <p>
  &middot; Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or related field
 </p>
 <p>
  &middot; 4+ years of experience in data engineering or ML engineering
 </p>
 <p>
  &middot; Hands-on experience with production-grade AI/ML systems
 </p>
 <p>
  ---
 </p>
 <p>
  Nice-to-Have
 </p>
 <p>
  &middot; Experience with reinforcement learning or planning systems
 </p>
 <p>
  &middot; Background in distributed systems design
 </p>
 <p>
  &middot; Contributions to open-source AI/data projects
 </p>
 <p>
  &middot; Certifications in AWS (e.g., Solutions Architect, Machine Learning Specialty)
 </p>
 <p>
  ---
 </p>
 <p>
  What You&rsquo;ll Build
 </p>
 <p>
  &middot; Autonomous data pipelines that self-heal and optimize
 </p>
 <p>
  &middot; AI agents capable of reasoning over enterprise data
 </p>
 <p>
  &middot; Scalable LLM-powered applications integrated with business workflows
 </p>
 <p>
  &middot; Intelligent systems that move beyond automation into decision-making
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  For more information on benefits and what we offer please visit us at
  <u>
   https://www.exlservice.com/us-careers-and-benefits
  </u>
 </p>
</div>


Agentic AI Data Engineer

VeeRteq Solutions Inc.

<div><p>We are seeking a high-caliber <b>AI Tech Lead / AI Engineer</b> to design, build, and operationalize agentic AI solutions that accelerate analytics and reporting delivery. This role goes beyond basic agent creation and requires hands-on experience with agent orchestration, memory, and enterprise-grade data access patterns, delivering scalable components that fit into an existing framework while rapidly adapting to incoming business requests.</p>
<p></p><p><b>Responsibilities: -</b></p>
<ul><li>Design, Architect, implement, and iterate on agentic AI solutions to shorten the cycle time for analytics, log analysis, and reporting requests.</li>
<li>Design agent orchestration patterns (multi-agent workflows), tool/function calling, and memory approaches appropriate for enterprise deployments.</li>
<li>Define secure and scalable data access patterns for agents (retrieval, context building, and grounding), integrating with existing data sources and governance expectations.</li>
<li>Partner closely with product, analytics, and engineering stakeholders to intake requirements quickly and deliver working prototypes and production-ready solutions.</li>
<li>Engineer reusable components and best practices that enable scalable delivery (not one-off scripts), aligned to an existing base framework.</li>
<li>Operationalize solutions for reliability and maintainability: testing strategies, monitoring/observability, prompt/version management, and deployment automation.</li>
<li>Evaluate build vs. buy options pragmatically when needed, while keeping focus on shipping solutions on the current platform stack.</li>
</ul><p></p><p><b>Tech Stack (Core): -</b></p>
<ul><li><b>Cloud:</b> AWS (primary deployment environment; open to alternatives)</li>
<li><b>Data/Analytics Platform:</b> Databricks (including native &quot;chat with data&quot; capabilities and potential agent integrations)</li>
<li><b>Agent Frameworks:</b> LangChain, LangGraph</li>
<li><b>Conversational analytics patterns:</b> Ask-questions-on-data / conversational BI approaches (agent-driven analytics and dashboards</li>
</ul><p></p><p><b>Experience: -</b></p>
<p>10+ Years</p>
<p></p><p><b>Location: -</b></p>
<p>Rosemont, IL (3days/Week)</p>
<p></p><p><b>Educational Qualifications: -</b></p>
<p>Engineering Degree BE/ME/BTech/MTech/BSc/MSc.</p>
<p>Technical certification in multiple technologies is desirable.</p>
<p><b>Skills: -</b></p>
<p><b>Mandatory skills</b></p>
<ul><li>Demonstrated experience delivering agentic AI solutions beyond prototypes, including enterprise deployment considerations.</li>
<li>Strong hands-on engineering background with AWS-based deployments.</li>
<li>Experience working with modern data platforms (e.g., Databricks) and integrating LLM solutions with analytics/data ecosystems.</li>
<li>Ability to operate as a senior individual contributor who can define architecture and implement key pieces end-to-end.</li>
</ul><p>Excellent communication and collaboration skills with US-based stakeholders</p>
<p><b>Skills &amp; Expertise Needed</b></p>
<ul><li><b>Agentic </b><b>AI engineering:</b> building and deploying LLM-powered agents for real business workflows.</li>
<li><b>Agent orchestration:</b> designing multi-step and/or multi-agent flows; managing tool use, control flow, retries, and failure handling.</li>
<li><b>Agent memory:</b> short-term and long-term memory patterns; conversation state; summarization and context window management.</li>
<li><b>Enterprise data access patterns for agents:</b> retrieval/grounding strategies; context assembly from structured and unstructured sources; performance-conscious access.</li>
<li><b>Production deployment mindset:</b> security, reliability, monitoring, and maintainability for enterprise-grade AI services.</li>
<li><b>Architecture &amp; best practices:</b> ability to design scalable components that fit into an existing framework and can be extended by the team.</li>
<li><b>Rapid requirements intake:</b> quickly translating ambiguous reporting/analytics asks into implementable solutions and iterating with stakeholders.</li>
<li><b>High autonomy:</b> tech-lead level capability without direct people management; self-directed and able to set engineering direction for the workstream</li>
</ul><p></p><p><b>Good-to-Have Skills</b></p>
<ul><li>Experience implementing retrieval-augmented generation (RAG) and hybrid retrieval across structured/unstructured sources.</li>
<li>Experience with LLMOps practices: prompt/version management, automated evaluation, and regression testing.</li>
<li>Experience building observability for AI systems (quality metrics, traces, latency/cost monitoring).</li>
<li>Familiarity with Databricks-specific agent or model serving patterns (where applicable).</li>
</ul><p>Experience building lightweight analytics experiences on top of agent outputs (e.g., auto-generated insights/dashboards).</p></div>

AI Tech Lead / AI Engineer

NorthBay - Pakistan

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


Azure AI (Agentic) Specialist - Team Lead

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