genai data engineer

The Hartford

<div>Sr Staff Data Engineer - GE07DE
We&rsquo;re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals &ndash; and to help others accomplish theirs, too. Join our team as we help shape the future. 
Join our team as a Sr GenAI Data Engineer and lead the charge in developing cutting-edge AI solutions and data engineering strategies. Embrace our core values of innovation, collaboration, and excellence as you unlock unparalleled growth opportunities in the dynamic field of AI and data engineering. Shape the future of technology with us! Apply now to be part of our innovative journey and make a significant impact!
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).<h2 class="jobSectionHeader">
Key Responsibilities:</h2>
Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices. Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure. Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions. Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems. Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar. Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc. Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management. Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies. Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems. Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns. Apply AI solutions to insurance-specific data use cases and challenges. Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.
Required Skills &amp; Experience:<ul><li>
8+ years&rsquo; Strong hands-on experience programming skills in Python.</li><li>
7+ years of data engineering Strong hands-on experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark.</li><li>
3+ years of data engineering experience focused on supporting Generative AI technologies.</li><li>
2+ years Strong hands-on experience implementing production ready enterprise grade GenAI data solutions.</li><li>
3+ years&rsquo; experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.</li><li>
3+ years&rsquo; Experience of vector databases and graph databases, including implementation and optimization.</li><li>
3+ years&rsquo; Experience in processing and leveraging unstructured data for GenAI applications.</li><li>
3+ years&rsquo; Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph).</li><li>
3+ years&rsquo; Experience with building AI pipelines that bring together structured, semi-structured and unstructured data. This includes pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and getting the data ready for Models and Agentic solutions.</li></ul> 
Nice to Have:<ul><li>
Experience with prompt engineering techniques for large language models.</li><li>
Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform.</li><li>
Experience in multi cloud hybrid AI solutions.</li><li>
AI Certifications Experience in P&amp;C or Employee Benefits industry Knowledge of natural language processing (NLP) and computer vision technologies.</li><li>
Contributions to open-source AI projects or research publications in the field of Generative AI.</li></ul>
Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford&rsquo;s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$135,040 - $202,560
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age</div>

Lead Gen AI Data Engineer

malomatia

<div>
 
 Role Summary
 
 
 
 
 
 You will lead the security architecture, governance, and assurance of our AI and GenAI platforms across the organization. This includes classical ML systems and modern LLM/agentic architectures. You will define how models are designed, deployed, monitored, and defended; ensure they are robust, explainable, privacy-preserving, and compliant; and act as the go-to expert for AI security across products, data, cloud, and security teams.
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 &bull;AI Security Architecture
 
 
 oDesign and review secure architectures for ML/LLM workloads (training, fine-tuning, inference, RAG, agents, plugins, tool calling, APIs).
 
 
 oDefine reference architectures for on-prem, hybrid, and cloud AI platforms (Azure OpenAI, AWS Bedrock, GCP Vertex, self-hosted models, etc.).
 
 
 &bull;Threat Modeling &amp; Risk Management
 
 
 oPerform AI-specific threat modeling (e.g., data poisoning, model theft, prompt injection, jailbreaks, supply-chain, inference attacks) using MAESTRO or similar framework.
 
 
 oAlign controls with leading frameworks: NIST AI RMF, ISO/IEC 27001, ISO/IEC 27090, ISO/IEC 42001, OWASP GenAI / LLM Top 10, CSA &amp; MITRE ATLAS.
 
 
 &bull;Security Control Design &amp; Implementation
 
 
 oDefine and oversee implementation of controls for:
 
 
 &squf;Training &amp; data pipelines (data quality, provenance, labeling, PII protection).
 
 
 &squf;Model &amp; artifact integrity (signing, SBOM, secure registries).
 
 
 &squf;Access control, isolation, rate limiting, and abuse detection.
 
 
 &squf;Secure prompt engineering and guardrail policies.
 
 
 &squf;Security prompt monitoring to detect ongoing attacks.
 
 
 &squf;Data security: data classification, data masking and DLP.
 
 
 &squf;MCP server hardening.
 
 
 &bull;Reliability &amp; Trustworthiness
 
 
 oPartner with engineering and data science to embed robustness, observability, fallback strategies, and evaluation pipelines (safety, bias, toxicity, hallucination monitoring).
 
 
 oContribute to SLOs/SLAs for AI systems, including security and reliability KPIs.
 
 
 &bull;Secure SDLC for AI
 
 
 ombed AI security into CI/CD: scanning, dependency checks, policy-as-code, red-teaming AI components pre- and post-release.
 
 
 &bull;Incident Response &amp; Red Teaming
 
 
 oLLM bias detection.
 
 
 oPerform red teaming activities to abuse and force AI hallucinations.
 
 
 oDevelop and maintain AI-specific playbooks (prompt abuse, model exfiltration, data leakage, compromised agents).
 
 
 oLead or support AI red/blue/purple teaming exercises using frameworks like MITRE ATLAS.
 
 
 &bull;Governance, Compliance &amp; Policy
 
 
 oAdvice on alignment with emerging AI regulations and standards (e.g., EU AI Act, regional laws, internal AI use policies).
 
 
 oDefine internal policies on responsible AI, data usage, model lifecycle, and 3rd-party AI risk management.
 
 
 &bull;Stakeholder Leadership
 
 
 oRun workshops, training, and awareness for engineering, security, and business teams.
 
 
 
 
 
 Required Qualifications &amp; Experience
 
 
 
 
 
 &bull;8&ndash;12+ years in Cybersecurity, with 3&ndash;5+ years focused on AI/ML or data platforms (can be overlapping).
 
 
 &bull;Hands-on experience with:
 
 
 oCloud platforms (Azure, AWS, GCP) and their AI services.
 
 
 oAt least one Agentic/GenAI stack (e.g., Transformers, LangChain/LlamaIndex, vector DBs, model gateways, MLOps platforms).
 
 
 &bull;Proven track record designing or reviewing secure architectures for:
 
 
 ML pipelines, LLM/RAG systems, or agentic/automation platforms.
 
 
 &bull;Strong understanding of:
 
 
 oCryptography, identity &amp; access management, network &amp; app security.
 
 
 oData protection &amp; privacy (PII, PHI, DPIA concepts).
 
 
 &bull;Experience working with or mapping to frameworks/standards such as:
 
 
 oNIST AI RMF, ISO/IEC 27001, ISO/IEC 42001, SOC 2, OWASP Top 10 &amp; OWASP GenAI/LLM Top 10, MITRE ATT&amp;CK/ATLAS, CSA guidance.
 
 
 &bull;Excellent communication skills: able to translate complex AI risks into clear business and technical requirements.
 
 
 Core Technical &amp; Domain Skills
 
 
 &bull;AI/ML &amp; GenAI fundamentals:
 
 
 oModel types (LLMs, encoders, diffusion, classical ML), training/inference flows.
 
 
 oData pipelines, feature stores, embeddings, vector databases.
 
 
 &bull;AI Penetration testing:
 
 
 oPrompt injection, model tampering, data poisoning, output manipulation, exfiltration, shadow AI, insecure plugins/integrations.
 
 
 &bull;Platform &amp; Infra:
 
 
 o Kubernetes, containers, API gateways, secrets management, zero trust.
 
 
 &bull;Observability:
 
 
 o Logging, tracing, safety &amp; quality metrics for AI systems.
 
 
 o Health and latency monitoring.
 
 
 &bull;Strong scripting/automation (Python preferred) for security tooling and assessments.
 
 
 Certifications &amp; Training (Required / Highly Desirable)
 
 
 
 
 
 Essential:
 
 
 
 
 
 &bull; One or more core security certifications:
 
 
 o CISSP, CISM, CCSP, ISO 27001 Lead Implementer/Lead Auditor.
 
 
 &bull;One or more cloud security certifications:
 
 
 oCCSK (Cloud Security Alliance), AWS Security Specialty, Azure Security Engineer, Google Professional Cloud Security Engineer.
 
 
 &bull;AI &amp; AI Security&ndash;specific training / certs (or commitment to obtain within 6&ndash;12 months):
 
 
 oNIST AI RMF or ISO/IEC 42001-focused training.
 
 
 oCertified AI Security Professional (CAISP / similar offerings that cover LLM/GenAI threats, MITRE ATLAS, OWASP LLM Top 10).
 
 
 oOffSec / similar LLM &amp; AI Red Teaming or GenAI security courses.
 
 
 oVendor AI/ML certifications (Azure AI Engineer, AWS Machine Learning Specialty, GCP ML Engineer) with demonstrated security emphasis.
 
 
 Additional desirable:
 
 
 &bull;GIAC/GWAPT/GXPN/GCLD or similar offensive / cloud / Appsec certs.
 
 
 &bull;Formal training in:
 
 
 oSecure MLOps &amp; ML supply-chain security.
 
 
 oPrivacy engineering &amp; data protection (e.g., CIPT, CDPSE).
 
 
 oOWASP GenAI / LLM Top 10, MITRE ATLAS, CSA MAESTRO &amp; other AI risk frameworks.
 
</div>

Artificial Intelligence Consultant

Jaseci Labs

AI Software Engineer - Jaseci LabsAbout UsWe're a cutting-edge AI technology company partnering with enterprise clients to deliver production-grade GenAI solutions. Our high talent-density team comprises Professors and Ph.D.s from University of Michigan and other universities to develop innovative production-grade software that serves millions of users and creates substantial business value.We&rsquo;re building in the open and pushing the frontier of agentic AI. As the creators of the Jaseci ecosystem and the Jac programming language (https://www.jaseci.org/), we&rsquo;re redefining how developers build intelligent systems&mdash;bringing AI, orchestration, and application logic into a single unified stack. Our open-source platform is used to rapidly prototype and deploy scalable, production-grade AI agents, and we&rsquo;re actively shaping a new paradigm for AI-native software development.Position OverviewWe're seeking talented AI Software Engineers to join our team in Ann Arbor and Detroit, Michigan. As an AI Software Engineer, you'll help develop and deploy advanced AI systems for enterprise clients like Ally Bank, contributing to open-source technology while working in a collaborative environment with industry experts and academic leaders.Key Responsibilities<ul><li>Design, develop, and deploy production-grade AI software systems</li><li>Collaborate with enterprise customers to understand requirements and deliver solutions that scale to millions of users</li><li>Work alongside academic and industry leaders in the AI space, including professors and Ph.D.s from the University of Michigan</li><li>Implement cutting-edge GenAI technologies into usable, scalable applications</li><li>Help create solutions that generate millions of dollars in value for enterprise customers</li></ul>Qualifications<ul><li>Strong programming skills (Python, JavaScript, or similar languages)</li><li>Experience with tools and open-source AI/ML models like Hugging Face, OpenAI API, or LangChain</li><li>Experience in AI/ML model training and evaluation: training data preparation and evaluation for ML models</li><li>Familiarity with model quantization and fine-tuning techniques like LoRA or prompt tuning is preferred</li><li>Experience with building software with GenAI models is required</li><li>Excellent problem-solving and analytical skills</li><li>Effective communication and collaboration abilities. Experience working in enterprises is preferred.</li><li>Eagerness to learn and adapt to emerging technologies</li></ul>For Internship Candidates<ul><li>Currently pursuing an undergraduate or graduate degree in Computer Science, Data Science, or related field</li><li>Basic understanding of AI concepts and programming fundamentals</li><li>We offer a clear intern-to-full-time pathway for exceptional performers</li></ul>For Full-Time Candidates<ul><li>Undergraduate or graduate degree in Computer Science, Data Science, or related field</li><li>Previous experience with AI/ML projects or coursework</li><li>Software development experience</li></ul>What We Offer<ul><li>Opportunity to work on AI systems that solve real-world problems for enterprise clients</li><li>Mentorship from industry professionals and University of Michigan faculty</li><li>Collaborative environment with leading AI researchers and engineers</li><li>In-person office in downtown Ann Arbor and Detroit.</li><li>Tremendous career growth opportunities in a rapidly evolving field</li><li>Competitive compensation and benefits</li></ul>Join us in developing the next generation of AI solutions that transform how enterprises operate and serve their customers!Job Type: Full-timePay: $60,000.00 - $115,000.00 per yearWork Location: Hybrid remote in Detroit, MI 48226

AI Software Engineer

Openkyber

<div>Role: GenAI Engineer Locations: Alpharetta, GA (Hybrid Onsite) Duration: 12+ Months Contract F2F Interview MUST Note: Candidate needs to be in the office 3-4 Days every week. Local or candidates from adjacent states only. 
Role Overview: Candidates must have experience delivering enterprise AI solutions in production environments (NOT only POC or personal projects/ Educational Projects) We are seeking a Senior GenAI Engineer with strong experience in machine learning, generative AI and enterprise scale AI platform development. The ideal candidate should have hands-on experience building production grade AI systems including Retrieval Augmented Generation (RAG) platforms, vector search pipelines, autonomous AI agents and scalable ML model deployment. The role requires expertise in Python based ML development, LLM frameworks, vector databases and AI orchestration frameworks such as LangChain, LangGraph and Hugging Face. 
Required Skills: Experience with enterprise level projects only. Strong Python development experience 7 years. Hands-on experience with RAG Vector, DB Embeddings and document chunking, Semantic search pipelines. Experience with LangChain, LangGraph and Hugging Face. Experience with Pandas, NumPy and data preprocessing pipelines. Experience deploying ML models as REST APIs and integrating AI with enterprise systems. 
Preferred Skills: Experience with Natural Language Processing NLP and Deep Learning Familiarity with Transformers and Large Language Models LLMs Experience with Cloud ML platforms such as Azure AI, AWS SageMaker, etc. 
Nice to Have: Experience building AI agents or autonomous systems. Knowledge of vector databases Pinecone Weaviate Milvus FAISS. Experience with MLOps practices Docker and Kubernetes. Exposure to multimodal AI systems. 
In compliance with the salary transparency law, the expected pay range for this role is $57.00 $62.00/hr. Actual compensation depends on experience and interview evaluation.
For applications and inquiries, contact: hirings@openkyber.com</div>

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