Role Description Tiger Analytics is looking for a highly skilled AI Engineer with 7+ years of experience in software engineering, with a heavy focus on Python, AWS infrastructure, and Generative AI. The ideal candidate will be responsible for building high-performance API services and implementing complex RAG and Agentic AI architectures. Qualifications - Minimum of 7+ years of professional experience in software development and AI engineering. - Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers. - Experience with DevOps, CI/CD pipelines, and ML pipelines within the AWS ecosystem. - Exposure to building Gen AI/Agentic AI applications, managing efficiency, latency, and backend infrastructure. - Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration. - Experience working with Bedrock Agent/Core services is a significant plus. Requirements - Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators. - Expertise in latency optimization and relevance tuning to ensure production-grade performance. - Strategic approach to document chunking and embedding, balancing granularity with semantic coherence. - Practical experience developing autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel. - Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs. - Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing. - Familiarity with evaluation frameworks (e.g., RAGAS, TruLens) to assess performance, grounding accuracy, and hallucination detection. - Ability to iterate systems based on performance metrics and continuous improvement practices. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Company Description Tiger Analytics is a fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

Role Description The Value Engineer – Applied AI sits at the intersection of sales, product, customer success, and enterprise AI deployment. This is a hybrid role that blends traditional value engineering with the hands-on, embedded delivery model of a forward deployed AI engineer. You will help customers understand, quantify, and realize the measurable business value of Sapiens' AI-powered solutions — and then roll up your sleeves to help them actually get there. You will partner with account teams and executive stakeholders to build compelling value cases, accelerate deal cycles, and go deeper with customers to prototype, deploy, and iterate on AI-driven workflows that deliver real outcomes. Key Responsibilities - Pre-Sales Value Strategy & AI Discovery: - Partner with sales teams to uncover customer pain points, strategic initiatives, and AI readiness. - Lead discovery sessions with customer executives to map business processes, KPI gaps, financial drivers, and high-value AI use cases. - Build tailored business cases, including ROI models, TCO analysis, and AI impact scenarios that quantify the value of intelligent automation and decision support. - Present value insights and AI deployment strategies to senior stakeholders in a compelling and consultative way. - Embed with customers during the sales cycle to prototype AI-powered workflows and demonstrate value before the ink dries. - Deal Acceleration & Execution: - Align Sapiens' AI capabilities to measurable business outcomes tied to customer priorities. - Collaborate with product experts, solution consultants, and engineering teams to map AI value drivers to platform features and deployment patterns. - Support competitive positioning by quantifying AI differentiators and the financial benefits of an AI-native delivery model. - Provide thought leadership during key engagements, executive briefings, and AI value workshops. - Build working proofs-of-concept and demonstration environments using Sapiens' AI tools to make the value tangible, not theoretical. - Forward Deployed AI Execution: - Embed directly with strategic customers post-sale to accelerate AI adoption and time-to-value. - Work inside customer environments to build, iterate, and ship production-ready AI applications on the Sapiens platform. - Identify repeatable AI deployment patterns across customer engagements and codify them into reusable playbooks for the broader team. - Act as the connective tissue between the customer's operational teams and Sapiens' product and engineering organizations — translating field insights into product direction. - Operate with autonomy and thrive under ambiguity; this role requires someone who can define what good looks like, not just follow a playbook. - Post-Sale Value Realization: - Partner with Customer Success to track actual AI-driven outcomes against proposed value models. - Build value realization reports for QBRs, renewals, and expansion opportunities — grounded in real deployment data, not projections. - Identify patterns across accounts to refine value frameworks and contribute field-level insights to the product roadmap. - Tools, Research & Enablement: - Maintain and evolve ROI calculators, AI impact benchmarks, and value frameworks specific to the insurance industry. - Train sales and customer-facing teams on value-selling methodologies and AI deployment best practices. - Conduct market and industry research to inform benchmarking and persona-specific AI value narratives. - Stay current on the latest LLM capabilities, agentic AI frameworks, and enterprise deployment patterns — and bring that knowledge into every customer engagement. Qualifications - 7+ years in value engineering, management consulting, financial analysis, solution consulting, or a related strategic role. - Demonstrated experience deploying or implementing AI/ML solutions in enterprise environments — not just advising on them. - Strong analytical and financial modeling skills (ROI, TCO, KPI modeling). - Exceptional communication skills, including executive-level storytelling, live demos, and technical presentation. - Ability to translate complex AI and technical capabilities into concrete business outcomes. - Experience engaging with C-suite stakeholders in enterprise environments. - Hands-on fluency with LLMs, prompt engineering, and AI product development — comfort building as well as advising. - Comfort working cross-functionally in a fast-paced SaaS or technology environment. - Experience in insurance, financial services, or another regulated enterprise vertical is a strong plus. Benefits - At Sapiens, we are dedicated to building a diverse, equitable, and inclusive work environment. - We believe that diverse perspectives, backgrounds, and experiences make us stronger and more innovative. - We are committed to creating a culture where every individual is valued and can thrive regardless of their race, ethnicity, gender, age, sexual orientation, gender identity, religion, disability, or any other characteristic. Company Description Sapiens is an E-Verified & Equal Opportunity / Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Role Description Cityblock is putting AI directly into the hands of the care teams and members we serve. You are a full-stack product engineer who takes an AI-native idea from a rough prototype to a feature running in production, in front of real clinical users, and you contribute to the prototyping loop that lets product and design move at that speed. Most of the value of AI in our product is still undiscovered. Your job is to shorten the distance between an idea and something people can actually use, and then to productionize effective use of AI into features that hold up in a regulated healthcare product. Reporting into the Product Engineering org, this role covers system design, including the LLM/SDK integration underneath, the evals and golden datasets that tell you whether it's working, and the UX. You embed with product, design, and work with clinical operations. Because these features run in a regulated healthcare product in front of real members and care teams, you help decide where AI acts on its own, where it stays advisory with a human in the loop, and how we prove a feature is safe to trust, designing for compliance from the start. Responsibilities - Implement full-stack feature work that integrates LLM APIs and SDKs into member- and care-team-facing product surfaces. - Own features end to end: system design, model/SDK integration, evals, and the UX that determines whether the feature is actually trusted and used. - Build observability and evals alongside the feature, so quality can be measured and then improved. - Apply and help improve the team's prototyping loop, eval discipline, and quality bar through the work you ship. - Put prototypes in front of real users early, learn from what breaks, and harden the ones worth keeping into production. - Bring an honest read of what's feasible back to product and design, so the roadmap reflects reality. - Work with product management, design, and clinical operations to find and understand the high-value AI opportunities behind the features you build. - Partner with the data organization for the grounded, trustworthy context your features depend on. Qualifications - 4+ years of experience as an engineer. - You are a strong full-stack product engineer who ships. You solve problems by building working software. - Experience integrating LLM APIs or SDKs into a shipped product, or closely related production experience you can build on. - Strong product sense: you care about whether people use your products and whether they provide measurable value. - Comfort owning ambiguity by taking a well-scoped, high-value idea and turning it into something real, with decreasing guidance over time. - Experience building evals or quality measurement for AI features, or the clear instinct that you need to. - Fluent daily use of AI assistants for engineering, with a clear sense of when to trust them and when not to. - Drawn to mission-oriented work, and comfortable partnering with clinical and design experts whose expertise differs from yours. Nice to Have - A CS degree or equivalent. - Prior work in a regulated or compliance-heavy environment (HIPAA, SOC 2, or similar). - Experience building AI-native product features from scratch, including the evals around them. - Design sensibility strong enough to prototype UX yourself. - Exposure to clinical operations or working alongside clinical staff as end users. - Hands-on with retrieval-augmented generation (RAG): embeddings, vector search, and grounding LLM output in trusted context. - Familiarity with agentic patterns including tool/function calling, structured outputs, and multi-step orchestration. - Experience with LLM eval and observability tooling (e.g., Braintrust, LangSmith) and LLM-as-judge techniques. - Comfort in a modern TypeScript/Node/React stack, including streaming and latency-sensitive LLM UX. Benefits - This role is eligible for health insurance, life insurance, retirement benefits, participation in the company’s equity program, paid time off, including vacation and sick leave. Salary Information The expected salary range for this position is: $139,000.00 - $183,000.00 Annual. Diversity and Inclusion Cityblock values diversity as a core tenet of the work we do and the populations we serve. We are an equal opportunity employer, indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information, or any other protected characteristic.

Role Description We are seeking an AI Engineer – Data & AI Platform to architect, build, and operationalize scalable generative AI and machine learning solutions across Snowflake, Databricks, and modern MLOps ecosystems. This role will partner with data scientists, ML engineers, and platform teams to design and deploy end-to-end AI/ML pipelines, advance AI integration, and ensure production-grade reliability for AI-driven products. The ideal candidate has 8+ years of experience in AI/ML engineering, with deep expertise in generative AI deployment, API-based AI services, large-scale data processing, and AI lifecycle management. The AI Engineer will not only deliver hands-on technical solutions but also set technical direction, mentor other engineers, and drive innovation across Teladoc's AI platforms. Essential Duties and Responsibilities - Operationalize GenAI and LLM applications, leveraging RAG (retrieval-augmented generation), vector search, prompt engineering, agentic AI, and MCP (Model Context Protocol). - Lead the design, development, and deployment of production-grade LLM and ML pipelines, including data transformation, feature engineering, training, tuning, and serving. - Architect scalable data and AI workflows on Snowflake, Databricks, and Azure ML, integrating AI models with modern data lakehouse platforms. - Build and maintain API-based AI services (FastAPI, Flask), enabling secure, performant, and reliable model access at scale. - Define and implement CI/CD pipelines for GenAI and ML services, using GitHub Actions/Azure DevOps, MLFlow, and container orchestration (Kubernetes, Docker). - Develop and enforce MLOps/LLMOps best practices, including experiment tracking, model versioning, observability, and governance. - Mentor ML engineers and data scientists on engineering rigor, scalable design, and production-readiness. - Partner with cross-functional teams to integrate AI services into products, ensuring security, compliance, and resilience in regulated healthcare environments. - Troubleshoot production AI systems, analyzing inference latency, drift, and performance issues, and implementing preventive solutions. - Document and communicate architecture patterns, operational standards, and AI development frameworks across the organization. Qualifications - Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related field; equivalent work experience is acceptable. - 8+ years of experience in AI/ML engineering roles, with proven success in architecting and scaling production LLM/GenAI and ML systems. - Experience deploying LLM and GenAI solutions including RAG, vector database integration, and agentic/tool‑augmented LLM systems (LangChain, MCP, or similar frameworks). - Experience with Snowflake or Databricks, using one or both as core platforms for data processing or AI/ML workloads. - Proven track record in MLOps/LLMOps, including CI/CD pipeline automation, model serving, monitoring, and governance, using modern AI infrastructure tools such as Docker, Kubernetes, Azure ML, MLflow, and Terraform. - Proficiency in Python and SQL, with experience processing high‑volume datasets using big‑data tools such as Spark or equivalent distributed systems. - Ability to collaborate in cross-disciplinary teams (engineering, product, compliance, security) and deliver impact in regulated industries. Bonus Qualifications - Excellent communication skills to articulate complex GenAI/ML concepts to diverse audiences. - Strong leadership and mentorship abilities, fostering technical growth across teams. - Understanding of API-driven AI development, including Python-based API frameworks (FastAPI, Flask) or equivalent experience working with API development workflows. - Certifications in Snowflake, Databricks, Azure ML, or AI/ML platforms preferred. - Experience in healthcare AI applications and regulated AI deployment. Requirements - The base salary range for this position is $200,000 - $230,000. - This position is eligible for a performance bonus and benefits (subject to eligibility requirements). - We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. - All time off must be approved by your manager prior to use. - You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. - This applies to full-time positions only. - If you are applying for a part-time role, your recruiter can provide additional details. Benefits - As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. - Applicants who falsify information will be disqualified. - Teladoc Health will not sponsor or transfer employment work visas for this position. - Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.