agentic ai engineer

Eli Lilly

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
 
Organization Overview: 
Delivery, Devices, and Connected Solutions (DDCS) sits within Eli Lilly's Product Research & Development organization. We are a diverse team of scientists and engineers responsible for discovering, designing, and developing patient-centric drug delivery solutions across a broad range of modalities — from injection devices to novel routes of administration and nanomedicines. DDCS drives the drug delivery innovation agenda across early and late development to meet the needs of an expanding portfolio that spans small molecules, biologics, and nucleic acid therapeutics. 
  
 DDCS is organized around a matrix model with strong disciplinary and functional horizontals supporting innovation and commercialization verticals. Our vision is to get our medicines to more patients faster by accelerating reach and scale, guided by three strategic pillars: Delivery Systems, Robust & Sustainable, and Patient Experience + Outcomes. 
  
 The Digital Transformation and Data Science team within DDCS serves as a key foundation for DDCS's digital transformation efforts. The team helps make data work more effectively for the organization by turning information into faster insights, stronger decision-making, improved ways of working, and practical AI solutions embedded in everyday DDCS workflows. 
 
Position Overview:  
 The Senior Advisor, Agentic AI Solutions Engineer will partner with DDCS business functions to translate machine learning, statistics, scientific computing, and AI concepts into practical tools that improve speed, productivity, and impact across the organization. Operating within the Digital Transformation and Data Science team, this role will design, build, and deploy AI-enabled workflows, agentic scientific systems, knowledge extraction tools, and scientific ML capabilities that help colleagues turn complex technical information into actionable decisions. Fundamentally, you are energized by extremely large, complicated, real-world challenges and are excited about full-stack development developing and utilizing modern AI tools to produce genuine, trusted results.
 
Key Responsibilities : 
AI Solutions Engineering & Practical Tool Delivery 
 
<ul>
<li>Partner with business functions across DDCS to identify, prioritize, and scope high-value opportunities where AI, machine learning, and automation can improve speed, productivity, insight generation, and decision quality.</li>
<li>Translate stakeholder needs into practical AI tools, technical designs, acceptance criteria, and delivery plans that fit real scientific, engineering, and operational workflows.</li>
<li>Develop AI-enabled applications, services, and workflows that integrate models, data sources, document collections, and user-facing interfaces for decision support and workflow automation.</li>
</ul>
Agentic Scientific AI Systems & Knowledge Extraction 
 
<ul>
<li>Create reusable scientific agent skills, task harnesses, validators, run ledgers, and reproducibility controls that allow AI agents to execute diverse, long-running tasks reliably.</li>
<li>Build agentic knowledge extraction and question-answering systems for structured and unstructured technical content, including PDFs, Word documents, handwritten notes, design histories, experimental records, and regulatory-relevant evidence.</li>
<li>Design evaluation, monitoring, guardrails, and human-in-the-loop escalation patterns so agentic outputs are auditable, traceable, and appropriate for high-consequence technical decisions.</li>
<li>Apply knowledge graphs, data ontologies, and structured knowledge representation where they improve retrieval, traceability, and reuse.</li>
</ul>
 
 Data Strategy, Decision Support & Workflow Transformation 
 
<ul>
<li>Contribute to DDCS data and AI strategy by identifying reusable patterns, data needs, platform capabilities, and solution architectures that support digital transformation at scale.</li>
<li>Turn information from experiments, simulations, development documents, and business processes into faster insights, stronger judgment, and improved ways of working across innovation and commercialization efforts.</li>
<li>Communicate model predictions, evidence, assumptions, limitations, uncertainty, and recommended actions through clear visualizations, decision-support outputs, and quantitative business cases that influence solution adoption, workflow redesign, platform investments, and portfolio priorities.</li>
</ul>
 
 Reliability, Validation, MLOps & Responsible AI 
 
<ul>
<li>Champion software engineering best practices including version control, automated testing, CI/CD, containers, documentation, reproducibility, observability, and fit-for-purpose MLOps/agent-ops practices.</li>
<li>Develop validation, monitoring, documentation, and model-risk approaches aligned with intended use, responsible AI principles, GxP awareness, and regulatory expectations where applicable.</li>
<li>Leverage cloud infrastructure (and HPC/GPU resources where needed) to develop, test, deploy, and scale agentic workflows, document intelligence systems, and analytics applications.</li>
</ul>
 
 Cross-Functional Collaboration & Scientific Translation 
 
<ul>
<li>Partner across the DDCS matrix with drug delivery scientists, device engineers, formulation scientists, data scientists, AI application engineers, quality, clinical, regulatory, and business stakeholders. </li>
<li>Identify and prioritize high-impact opportunities where AI solutions, scientific ML, agentic workflows, or knowledge extraction can reduce development time, improve productivity, or mitigate technical and business risks. </li>
<li>Translate complex analytical and AI findings into clear narratives and quantitative business cases that influence solution adoption, workflow redesign, platform investments, and portfolio priorities. </li>
</ul>
 
 Capability Building, External Leadership & Mentorship 
 
<ul>
<li>Advance the DDCS technology roadmap for practical AI tools, document intelligence, agentic workflows, and reusable knowledge systems.</li>
<li>Share methods, reference patterns, and lessons learned that help DDCS embed data and AI into everyday work across scientific and business functions.</li>
<li>Mentor team members and partners on reliable agentic systems, responsible AI, and rigorous communication of model assumptions, uncertainty, and decision impact.</li>
<li>Stay current with the fast-moving agentic AI and LLM landscape and bring new tools, frameworks, and techniques into DDCS’s practice where they add real value.</li>
</ul>
Basic Qualifications 
 
<ul>
<li>Earned Master’s degree with a minimum 5 years post-degree experience in Computational/Computer Science, Machine Learning, Artificial Intelligence, Engineering, or a related quantitative field (or equivalent experience)</li>
<li>2+ years of applied technical work building AI or machine learning solutions in a programming language such as Python/R, with working knowledge of the ecosystem (NumPy, pandas, PyTorch, scikit-learn, or related).</li>
<li>3+ years of expertise in strategic thinking, problem framing, and translating ambiguous business or scientific needs into tractable AI, modeling, or computational workflows. </li>
<li>Demonstrated ability to frame ambiguous business or scientific needs as tractable AI, modeling, or computational workflows.</li>
<li>Skill in communicating technical recommendations with clearly stated assumptions, uncertainty, and limitations, to scientific, engineering, and business audiences.</li>
</ul>
Additional Preferences: 
<ul>
<li>Earned PhD in relevant field with 2+ years relevant experience</li>
<li>Experience applying AI/ML to healthcare, pharmaceutical, or life-sciences problems (prior biology or life-sciences background not required).</li>
<li>Strong SQL and relational data modeling, with comfort turning large, messy, unstructured, or incomplete data into reliable, decision-ready output.</li>
<li>Hands-on experience with cloud platforms and solid engineering practice: Git, containers, CI/CD, and experiment or run tracking. Comfort with GPU and HPC environments is a plus.</li>
<li>Experience with knowledge graphs, ontologies, or structured knowledge representation for technical content.</li>
<li>Evidence of contribution to significant work, ideally through publications at relevant ML/AI/NLP venues (NeurIPS, ICML, ICLR, ACL, EMNLP) or comparable open-source or applied contributions.</li>
<li>Fluency with agent frameworks and orchestration (LangGraph, AutoGen, CrewAI, or equivalent) and the primitives underneath them: planner/executor splits, hand-offs, escalation logic, and state management across multi-step or multi-session workflows. Knowing why they fail, not just how to call them.</li>
<li>End-to-end RAG design over messy technical documents: parsing and layout extraction from PDFs, scans, and tables; chunking strategy; hybrid search; reranking; embedding models; and vector stores (pgvector, Pinecone, Weaviate, or similar).</li>
<li>LLM engineering judgment: context design, tool/function calling (MCP or comparable standards), structured output design at scale, and knowing when to fine-tune versus retrieve versus prompt.</li>
<li>Evals engineering: golden datasets and benchmarks, automated regression suites, and failure-mode tracking. Evidence of a trustworthy agent to deploy.</li>
<li>LLMOps in production, treating cost, latency, and reliability as engineering constraints with the monitoring to match.</li>
<li>Guardrail and safety design for autonomous systems: approval gates, rollback logic, hallucination and drift detection, and model-risk thinking for high-consequence decisions.</li>
</ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
 
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).
 
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
 $129,000 - $209,000
 
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
 
#WeAreLilly

Senior Advisor, Agentic AI Solutions Engineer

TCP Software

<div>TCP is committed to cultivating a diverse and inclusive team. However, we are not able to sponsor visas for this role.
About TCP (TimeClock Plus):
For more than 30 years, TCP has helped organizations engage their people by providing flexible, mobile timekeeping and workforce management solutions. Trusted by tens of thousands of customers and millions of users, TCP delivers best-in-class technology and personalized support to organizations of all sizes in the public and private sector to meet their complex timekeeping, employee scheduling, leave management and other workforce needs. Growth is happening and our vision for a successful future is clear &ndash; We&rsquo;d love for you to join us on this journey! For more information on TCP, visit www.tcpsoftware.com or follow us on LinkedIn or Facebook.
As an Agentic AI Software Engineer you will:
<ul><li>Design, build, and ship agentic AI features end to end, from detection and decision logic through safe action execution, in a cross-functional agile environment</li><li>
Ground agent behavior in deterministic rules engines and governed data so every agent explains its reasoning and never acts outside permitted boundaries</li><li>
Build and operate the LLM layer, including prompt architecture, structured outputs, confidence scoring, timeouts, and rules-only fallback paths</li><li>
Implement safe patterns for agent actions, including idempotent operations, undo windows, retries with backoff, and immutable audit logging</li><li>
Develop statistical detection and baseline logic that turns workforce data into ranked, explainable findings with business impact attached</li><li>
Manage inference cost, latency, and model selection from development through production</li><li>
Partner with QA on evaluation suites, shadow-mode rollouts, and the trust metrics that gate every agent capability, and mentor junior engineers along the way</li><li>
Operate independently, setting priorities and goals while continuing to learn and grow technically</li></ul>
Our Technology Stack:<ul><li>
Backend: C# on modern .NET and .NET Framework in a multi-tier service architecture.</li><li>
Frontend: JavaScript and AngularJS, with Jasmine unit tests.</li><li>
Database: Microsoft SQL Server, including schema projects and idempotent migration scripts.</li><li>
Delivery: Docker, Jenkins CI/CD, and cloud-hosted deployment.</li></ul>
Requirements<ul><li>
6+ years of professional software development experience, including shipping LLM-backed or agentic features to production.</li><li>
Deep production experience with C#/.NET, SQL Server, and API design in systems where correctness has financial consequences, such as payroll, billing, or banking.</li><li>
Experience integrating LLM APIs into enterprise applications, with structured outputs, retrieval grounding, and evaluation-driven iteration.</li><li>
Working fluency with statistical techniques on time-series data, such as rolling baselines, outlier detection, and threshold tuning.</li><li>
The ability to understand requirements and solve technical issues without supervision, serving as a technical lead.</li></ul>
AI Experience Requirements:<ul><li>
Hands-on daily use of AI coding assistants or agentic tools, such as Claude Code, GitHub Copilot, or Cursor.</li><li>
Production experience with LLM APIs, MCP servers, or internal AI tooling.</li><li>
An understanding of human-in-the-loop agent design and write-capable AI.</li><li>
A clear understanding of LLM failure modes, including hallucination, prompt injection, and cost overrun, plus the limits and risks of AI-generated code.</li><li>
Preferred: experience with multi-agent orchestration, evaluation harness design, or statistical anomaly detection.</li></ul>
Physical Requirements:<ul><li>
Prolonged periods sitting at a desk and working on a computer.</li><li>
Must be able to lift up to 15 pounds at times.</li></ul>
Benefits<ul><li>
Competitive salary
</li><li>20 Days of PTO (Paid Time Off) and 13 days of companywide holidays</li><li>
8 hours to volunteer and impact the community</li><li>
Comprehensive benefits (Health/Dental/Vision/ 401K)</li><li>
Employee Choice Pre-Tax Benefit</li></ul>
TCP is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.</div>

Agentic AI Software Engineer United States

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
<div>Job Description
<div>Job Description
</div></div><div><div><div><div><div><div><div><div><div>ware engineers, product managers and solution engineers closely to design, implement and iterate agentic AI systems with customers.
 
 
With your strong technical competence, strategic thinking and customer engagement, you will innovate at the frontier of the field, having the opportunity to create new solutions and define new categories of product with meaningful impact to Salesforce customers and beyond.
 
 
We are looking for candidates who
<ul><li>Has exceptional engineering skills.
</li><li>Has deep ML knowledge with meaningful implementation track records.
</li><li>Prioritize deep and strategic thinking.
</li><li>Has dedication, patience and resilience to build exceptional product experience.
</li><li>Collaborative and win with teams.
</li><li>Proactive and bias to action, comfortable in fast-pacing environment.
</li><li>Competitive coding winner (ACM-ICPC, etc).
</li><li>Startup founders in agentic AI, LLM, area (e.g., YC backed startup)
</li><li>Programming &amp; Systems:
</li><li>Strong proficiency in Python; solid experience with C++ and/or Java
</li><li>Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
</li><li>Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
</li><li>Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
</li><li>Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance
</li><li>Strong software engineering fundamentals (data structures, algorithms, system design)
</li><li>Experience building production-quality systems
</li><li>Agentic / LLM Systems
</li><li>Practical experience with LLMs and agentic workflows (tool use, planning, memory, multi-step reasoning)
</li><li>Experience building end-to-end AI agents or complex AI-driven applications
</li><li>Familiarity with prompting, orchestration, and evaluation for LLM-based systems
</li><li>Machine Learning &amp; AI
</li><li>Hands-on experience with deep learning frameworks
</li><li>Strong understanding of ML fundamentals
</li><li>Experience implementing and debugging model training, evaluation, and inference pipelines
</li><li>Infrastructure &amp; Deployment
</li><li>Experience deploying ML systems using Docker and cloud platforms (AWS, GCP, or Azure)
</li><li>Familiarity with distributed training or inference and performance optimization
</li><li>A demonstrated, genuine AI-first approach to engineering. Using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
</li><li>Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows
</li><li>Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
</li></ul></div></div></div></div></div></div></div></div></div>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.&amp;#xa;&amp;#xa;The typical base salary range for this position is $148,500 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Senior Member of Technical Staff - AI Research

KeyBank

<div>Location:
4910 Tiedeman Road, Brooklyn Ohio
Department: Contact Center Technology 
Experience: 4+ years<h3 class="jobSectionHeader">
About the Role</h3>
KeyBank is seeking a Lead AI Engineer to design, build, and modernize AI-powered conversational experiences, IVR platforms, and Voice Bot solutions within the Contact Center Technology organization. This role serves as a senior hands-on engineer responsible for architecting, developing, and delivering AI-driven solutions that enhance customer self-service and agent experiences.
Unlike a traditional technical lead role, this position is deeply focused on hands-on AI engineering and solution delivery. The Lead AI Engineer will spend the majority of their time designing, building, coding, integrating, and optimizing AI-powered applications while providing technical guidance across initiatives.
The Lead AI Engineer partners closely with product, platform, voice, and operations teams to deliver secure, scalable, and highly reliable conversational AI solutions on Google Cloud Platform (GCP). This is a senior individual contributor role with delivery accountability, but no people management responsibility.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul><li>
Design and develop AI-powered IVR and voice bot solutions leveraging modern conversational AI frameworks.</li><li>
Lead the technical architecture, engineering design, and implementation of AI-driven customer experience initiatives.</li><li>
Build and develop Node.js / TypeScript microservices aligned to cloud-native and low-latency voice requirements.</li><li>
Own end-to-end delivery of complex AI features, from concept and design through deployment and production support.</li><li>
Apply agentic AI patterns utilizing Gemini, LangGraph, LangChain, and emerging AI frameworks to enhance conversational experiences.</li><li>
Develop, test, evaluate, and optimize prompts, workflows, and AI orchestration strategies.</li><li>
Collaborate across the contact center technology ecosystem to support call routing, self-service, and agent handoff scenarios.</li><li>
Provide technical mentorship and code review support while contributing directly to development efforts.</li><li>
Establish engineering best practices for AI solution development, testing, deployment, and observability.</li><li>
Apply SRE principles to ensure resiliency, scalability, monitoring, and production readiness.</li><li>
Ensure solutions comply with security and regulatory requirements (PII / PCI).</li></ul><h3 class="jobSectionHeader">
Required Skills &amp; Qualifications</h3><ul><li>
4+ years of software engineering experience, including 2+ years as a Lead AI Engineer, Lead Engineer, Principal Engineer, or comparable senior technical contributor role.</li><li>
Strong hands-on experience building and deploying AI-powered applications and services.</li><li>
Strong, hands-on experience with Node.js / TypeScript.</li><li>
Proven experience designing and delivering cloud-native solutions on GCP.</li><li>
Experience implementing and integrating LLMs, conversational AI platforms, and agentic AI frameworks.</li><li>
Solid understanding of microservices architecture, APIs, and distributed systems.</li><li>
Hands-on Kubernetes experience, including GKE cluster setup and platform operations.</li><li>
Experience with IVR, voice bots, conversational AI, or contact center technologies.</li><li>
Strong collaboration skills across engineering, product, and operations teams.</li><li>
Excellent technical judgment, communication, and problem-solving skills.</li></ul><h3 class="jobSectionHeader">
Preferred Qualifications</h3><ul><li>
Experience with conversational AI and agentic frameworks (Gemini, LangGraph, LangChain).</li><li>
Experience developing AI agents, orchestration workflows, and multi-agent solutions.</li><li>
Knowledge of voice flows, call routing, containment, and agent escalation.</li><li>
Experience working in regulated or financial services environments.</li><li>
Familiarity with CI/CD pipelines, containerization, and Infrastructure as Code.</li><li>
Experience working in Agile delivery models at enterprise scale.</li><li>
Demonstrated experience with Agentic &quot;Vibe Coding&quot; &mdash; rapid prototyping and iterative development using AI-assisted coding tools, prompts, and agent-driven workflows.</li></ul>
This position is NOT eligible for employment visa sponsorship for non-U.S. citizens.
COMPENSATION AND BENEFITS
This position is eligible to earn a base salary in the range of $96,000.00 - $181,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.
Please click here for a list of benefits for which this position is eligible.
Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.
Job Posting Expiration Date: 09/11/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.
Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com. 

#LI-Remote</div>

Lead AI Engineer

pointer infotech L.L.C

OverviewJoin our innovative team as an AI Engineer and be at the forefront of developing cutting-edge artificial intelligence solutions that transform data into actionable insights. In this dynamic role, you will design, implement, and optimize AI models and machine learning frameworks to solve complex problems across various domains. Your expertise will drive the deployment of scalable AI systems, leveraging big data technologies and cloud services to deliver impactful results. This position offers an exciting opportunity to work with advanced tools and methodologies in a collaborative environment dedicated to pushing the boundaries of AI innovation.Responsibilities<ul><li>Job Summary:</li><li>We are looking for an experienced AI Engineer / Senior AI Architect with strong expertise in Agentic AI, Conversational AI, and AI solution development. The ideal candidate will have hands-on experience building AI solutions across Microsoft and Google ecosystems.Key Skills &amp; Responsibilities:Develop Agentic AI solutions, conversational agents, and virtual assistants.Hands-on experience with Microsoft Foundry and Azure AI services.Experience with Azure AI Search, Azure AI Language, Power Platform, and Copilot Studio.Develop AI conversational solutions using Google Dialogflow CX, Google Conversational Agents, and Google CCAI Services.Build and integrate APIs and web services with AI applications.Experience with NLP, Generative AI, LLMs, and AI/ML.Develop and maintain SharePoint Online solutions using Microsoft Power Platform.Train, deploy, monitor, and optimize AI models.Create Looker dashboards for monitoring AI agent performance.Strong programming skills in C#, .NET, JavaScript, or Python.Ensure AI solutions follow security, privacy, governance, and responsible AI practices.Collaborate with business SMEs and cross-functional technical teams.Lead AI Proof of Concept (POC) initiatives and present AI solutions to stakeholders.Required Experience:5+ years of IT experience.2+ years of AI Conversational Agent implementation experience.1+ year of Power Platform experience.Mandatory: Agentic AI development using Microsoft Foundry.Mandatory: SharePoint Online + Microsoft Power Platform.Mandatory: Google Conversational Agents / Dialogflow CX / Google CCAI Services.Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent experience.*</li><li>No Visa sponsorship is available this time</li></ul>Pay: $65.00 - $70.00 per hourWork Location: In person

AI Engineer

Coforge

AI Engineer -Practitioners who build and deploy AI models and agentic workflows in production, including prompt engineering, fine-tuning, RAG pipelines, and AI-infused application development. These individuals design, develop, customize, and implement AI solutions for others to use. Technology - Java, Frontend and QE (Playwright).
 We are seeking an experiencedAI Engineer to design, develop, and deploy AI-powered applications and agentic workflows into production environments. The ideal candidate will have hands-on expertise in building AI solutions using Large Language Models (LLMs), Retrieval Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, and modern application development practices.
 This role requires a combination ofAI engineering, Java development, Frontend development, and Quality Engineering (Playwright) to deliver scalable, reliable, and enterprise-grade AI solutions.
 
Key Responsibilities
 
AI Solution Development
 
<ul>
<li>Design, develop, and deploy AI-powered applications using modern LLM technologies.</li>
<li>Build and implement agentic workflows leveraging AI agents, orchestration frameworks, and automation platforms.</li>
<li>Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.</li>
<li>Perform prompt engineering, prompt optimization, and model evaluation to improve AI solution accuracy and reliability.</li>
<li>Fine-tune foundation models where applicable to meet business-specific requirements.</li>
<li>Integrate AI capabilities into existing enterprise applications and platforms.</li>
<li>Monitor, optimize, and maintain AI systems in production environments.</li>
</ul>
Application Development
 
<ul>
<li>Develop backend services and APIs using Java-based frameworks.</li>
<li>Build responsive and scalable frontend applications to deliver AI-driven user experiences.</li>
<li>Collaborate with architects, product owners, and business stakeholders to translate requirements into technical solutions.</li>
<li>Implement integrations with internal and external systems through APIs and microservices.</li>
</ul>
Quality Engineering Testing
 
<ul>
<li>Develop automated test strategies for AI-enabled applications.</li>
<li>Design and execute UI and API automation using Playwright.</li>
<li>Validate AI outputs through functional, regression, and performance testing.</li>
<li>Establish test frameworks and quality gates for AI solutions deployed in production.</li>
<li>Ensure security, performance, and reliability standards are met.</li>
</ul>
Collaboration Innovation
 
<ul>
<li>Work closely with AI Architects, Data Scientists, Product Teams, and Business SMEs.</li>
<li>Stay current with emerging AI technologies, frameworks, and industry best practices.</li>
<li>Contribute to AI governance, responsible AI practices, and solution documentation.</li>
</ul>
Required Skills
 
AI GenAI
 
<ul>
<li>Prompt Engineering</li>
<li>Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.)</li>
<li>Agentic AI Frameworks</li>
<li>Retrieval-Augmented Generation (RAG)</li>
<li>Vector Databases</li>
<li>Model Evaluation and Optimization</li>
<li>Fine-tuning Concepts</li>
<li>AI Application Development</li>
<li>AI Orchestration Frameworks (LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, etc.)</li>
</ul>
Backend Development
 
<ul>
<li>Java 8+/11+/17+</li>
<li>Spring Boot</li>
<li>REST APIs Microservices Architecture</li>
<li>API Integration</li>
</ul>
Frontend Development
 
<ul>
<li>React.js / Angular / Modern JavaScript Frameworks</li>
<li>HTML5, CSS3, JavaScript, TypeScript</li>
</ul>
Quality Engineering
 
<ul>
<li>Playwright Automation</li>
<li>API Testing</li>
<li>Test Automation Framework Design</li>
<li>Functional Regression Testing</li>
<li>CI/CD Testing Practices</li>
</ul>
Cloud DevOps
 
<ul>
<li>Azure / AWS / GCP</li>
<li>Docker Kubernetes</li>
<li>CI/CD Pipelines</li>
<li>Git, GitHub, Azure DevOps</li>
</ul>

The Campbell's Company

<div>
 
 Since 1869, we've connected people through food they love. We&rsquo;re proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell&rsquo;s brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao&rsquo;s Homemade, Snack Factory, Snyder&rsquo;s of Hanover. Swanson, and V8.
 
 
 
 
 Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.
 
 
 
 
 Data Engineer / AI Engineer (Co-op)
 
 
 
 We are seeking a motivated and curious
 
 Data Engineer / AI Engineer
 
 to join our team. This co-op / internship offers hands-on experience at the forefront of Generative AI and automation. You will have the opportunity to learn and work with cutting-edge technologies within our Agentic Frameworks to refine their usage in a modern Databricks environment. If you are passionate about the future of AI and eager to build "intelligent" systems, we want to hear from you!
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Prototype AI Agents: Assist in building and testing AI agents designed to automate internal workflows or enhance data retrieval processes.
 </li>
 <li>
 AI Training: Provide feedback to enhance and optimize the output of agents.
 </li>
 <li>
 Prompt Engineering &amp; Tuning: Experiment with and refine system prompts to improve the accuracy and reliability of outputs.
 </li>
 <li>
 Monitor Model Performance: Identify "hallucinations" or inconsistencies in AI responses and suggest improvements for model grounding.
 </li>
 <li>
 Collaborate with Agile Teams: Work with cross-functional teams to integrate AI capabilities into existing enterprise applications and participate in Agile ceremonies.
 </li>
 <li>
 Explore Emerging AI Tools: Research and test new frameworks in the Agentic AI space under the guidance of senior AI and Data Engineers.
 </li>
 <li>
 Document AI Architectures: Help document model schemas, API integrations, and AI governance standards.
 
 
 </li>
 </ul>
 
 Learning &amp; Development Opportunities
 
 
 
 <ul>
 <li>
 Hands-on training in Generative AI and Agentic technologies.
 </li>
 <li>
 Mentorship from senior AI Engineers and Data Scientists working on enterprise-scale deployments.
 </li>
 <li>
 Practical experience building on Cloud/SaaS infrastructure (e.g., Azure, Databricks, Snowflake).
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Current graduate student in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field
 </li>
 <li>
 Foundational programming skills in Python and an understanding of SQL.
 </li>
 <li>
 Familiarity with AI concepts through coursework or personal projects.
 </li>
 <li>
 Excellent problem-solving skills and a high degree of technical curiosity.
 </li>
 <li>
 Eager to learn in a rapidly evolving field and able to adapt to new tools quickly.
 
 
 </li>
 </ul>
 The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.
</div>

Data Engineer, DA&AI Co-Op

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