Location: Remote - If based in NYC, will require office presence 2/3 days a week, for LATAM and European regions will be expected to work EST hours with a 5 hour overlap.

Remote/Hybrid | Full-time

Compensation: $140K - $200K

We are hiring on behalf of our client, an innovative technology firm who is seeking an experienced Full-Stack AI Engineer to join a growing, AI-focused engineering team. The client develops advanced intelligence and analytics solutions designed to help participants in digital asset markets make more informed decisions by combining financial data, automation, and modern AI technologies to transform complex information into actionable insights.

In this role, the successful candidate will work closely with product, research, and engineering leadership to develop next-generation, AI-powered financial applications. This is a highly collaborative position that requires strong ownership, technical depth, and the ability to move quickly from concept to production.

Key Responsibilities

Full-Stack Product Development

Location: Remote - EST timezone

Remote | Full-time

Compensation: $100K - $130K

We are hiring on behalf of our client who is seeking an exceptional, production-proven Infrastructure & DevOps Engineer to take absolute ownership of the deployment, secure networking, architectural lifecycle, and overall reliability of this distributed agent fleet from day one. The client is engineering a sophisticated infrastructure designed to launch a highly distributed fleet of managed, single-tenant personal artificial intelligence (AI) trading agents. Operating non-stop, these isolated processes execute high-frequency, complex financial workflows natively on blockchain infrastructure, dedicated exclusively to individual user portfolios.

Key Responsibilities

Description

Tiger Analytics is looking for experienced Forward Deployment Engineer (Generative AI) with Gen AI experience to join our 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 has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployment Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Tiger Analytics is looking for experienced Forward Deployed Engineer (Generative AI) with Gen AI experience to join our 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 has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployed Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Key Responsibilities-

Role Overview

We are seeking a high-caliber Site Reliability Engineer (SRE) to join our Forward Engineering team. You will be the guardian of our production ecosystems, ensuring that our complex, data-driven AI platforms remain resilient, scalable, and highly performant. This role is a hybrid of software engineering and systems architecture, with a specialized focus on MLOps—bridging the gap between model development and production-grade reliability.

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning 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 has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Senior Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Key Responsibilities

AI Engineer - Pentesting Agent

Location: Preference for the UK or US

Remote | Full-time

Compensation: Competitive

Our client is the fastest-growing online cybersecurity training platform in the industry, currently serving more than 6 million users and over 1,000 global businesses, including government agencies and Fortune 500 organizations. With a significant initial investment, the organization is developing a fully autonomous AI pentesting agent designed to plan, exploit, adapt, and report with the speed and precision required for modern offensive security.

The team is seeking a talented AI Engineer to join a small, high-impact group dedicated to building this autonomous system from the ground up. This role is ideal for a deeply curious engineer with a passion for AI agents and a strong interest in the cybersecurity domain. The successful candidate will design the core logic of the system, shaping its reasoning, memory, and execution flows to handle complex offensive security tasks reliably.

Key Responsibilities

Software Engineer (Backend & AI Infrastructure)

Location: San Francisco, CA

Hybrid | Full-time

Compensation: $160K – $300K + Equity

Our client is a venture-backed technology firm based in San Francisco that is redefining the global research industry through AI-powered user interviews. By leveraging advanced AI-moderated technology, the platform enables global enterprises to achieve deep qualitative insights at unprecedented speed and scale. Currently serving world-class brands across the technology and consumer sectors, our client is disrupting a $140B market by replacing slow, high-cost legacy services with high-performance automated solutions.

Following a breakout year characterized by 8x growth, the organization recently secured a $30M Series B funding round led by top-tier Silicon Valley investors. The engineering team is currently scaling to support the rapid adoption of AI-moderated research as the new industry standard. This is a high-impact opportunity for a Backend Software Engineer to join a lean, elite team of 30 in San Francisco and take ownership of mission-critical infrastructure.

Key Responsibilities

Tiger Analytics is looking for experienced GenAI Architect to join our 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 has been recognized by various market research firms, including Forrester and Gartner.

We are looking for a hands-on Engineering Lead with deep expertise in Generative AI (GenAI), Large Language Models (LLM) / Small Language Models (SLM) who can lead the design, development, and integration of AI-powered components into real-world, production-grade applications. This role demands strong engineering leadership and best practices, a practical approach to application development and system design with applied AI, fluency in modern AI tools, frameworks, cloud-native application stacks, and preferably knowledge of healthcare domain intricacies. You will lead the technical delivery of AI-powered features for a variety of horizonal and vertical healthcare use cases— all while ensuring compliance with enterprise integration standards.

Requirements

Responsibilities

Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.

We are looking for a highly skilled GenAI Engineer with strong hands-on experience in building, evaluating, and deploying advanced Generative AI systems. The ideal candidate will have deep expertise in agentic frameworks, model fine-tuning, and reinforcement learning, along with a strong focus on experimentation, reliability, and hallucination mitigation beyond prompt engineering.

Requirements