Software Engineer (AI Agents)

Akur8 is a fast-growing InsurTech scale-up on a mission to modernize how insurers assess, price, and manage risk. Our next-generation SaaS platform combines transparent machine learning, predictive analytics, and smart product design to turn complex insurance workflows into scalable, data-driven systems. Powered by expert engineering, data, product, and actuarial teams, Akur8 enables insurers to model risk up to 10x faster while maintaining transparency, explainability, and regulatory trust. As our product suite expands, we are building an end-to-end platform supporting pricing, reserving, and forward-looking risk decisions — helping insurers operate efficiently in a complex environment. Recognized globally, Akur8 has been featured in: CB Insights’ Insurtech 50 (2025) CNBC’s InsurTech Top 150 (2025) InsurTech100 Global Insurtech Top 100 (2025) Professional Equality Index 97/100 (2025) With 40+ nationalities across 8 global offices, we serve 320+ clients across 4 continents while maintaining a strong engineering and product culture. We are proud to be an equal opportunities employer, fostering an inclusive environment where diverse perspectives help shape better products and decisions. Akur8 is a global insurance technology company trusted by leading carriers. We build software that shapes billions of dollars in risk decisions every year, turning complex data into actionable intelligence at scale. Insurance pricing depends heavily on unstructured regulatory and market data — filings, forms, exhibits, bulletins, and countless other documents that are hard to search, interpret, and operationalize. We're building the OS for pricing: systems that reliably transform tens of millions of messy documents into queryable, trustworthy intelligence embedded directly in pricing workflows. Our AI team is small, talent-dense, and operates with real ownership. We maintain open-source projects with thousands of stars and publish work recognized across the AI ecosystem. The problems we work on are active research areas where no one has great answers yet. You'll own the full feedback loop: diagnose where the product falls short, rigorously analyze root causes, build evaluations, and ship improvements that customers feel. The work spans agent systems, evaluation and data quality, and production engineering in roughly equal measure. You'll work directly with customers when it helps you understand the problem deeply - we believe engineers should have a clear line of sight to the people using what they build. The type of projects that you can expect to work on: Design and refine tool-calling patterns and agent orchestration to handle multi-step research tasks that requires reasoning across thousands of related documents. Build ingestion and normalization systems for complex structured documents at scale - millions of filings where formats vary and each version builds on the last. Build and iterate on reinforcement fine-tuning harnesses , including training graders for research tasks with non-verifiable reward. Develop tooling to measure, profile, and optimize agent pipeline performance - latency, cost, and quality across millions of calls. Run experiments end-to-end : design, analyze, and translate into clear product recommendations. Why this role ? You'll work on genuinely hard, unsolved problems at the intersection of AI systems and a massive real-world data domain. You'll ship to production regularly, talk to customers, and see your work change how people make consequential decisions . The team is small enough that your judgment directly shapes the product - and we're building it to be best in class. *This role is a hybrid position to be based in New York City, with a necessity for 3 days a week of office presence. Candidates must be team players with strong interpersonal skills, as well as: 2 - 5 years of experience building software professionally, with strong programming fundamentals (we work mostly in Python). Proficiency with LLM APIs, agent frameworks, and modern retrieval patterns. You stay current as the field moves. We don't need classical ML expertise - we need someone on the frontier of applied AI. Strong track record of shipping high-impact work in ambiguity . You take a vague problem, define what "good" looks like, ship a v0, and iterate. Experience shipping user-facing products , either backend or full-stack. Drawn to the question "how do we know this is actually better?" - excited to build the evaluation infrastructure that answers it rigorously. Curiosity over domain experience. No insurance background needed - you learn fast and care about understanding the problem space deeply. Strong written and spoken English As a newcomer, you'll be joining a diverse, highly skilled and motivated team, with a strong Tech DNA, colleagues that are eager to share their knowledge and passion. We care about strong teamwork and a positive day-to-day environment. The team regularly connects through optional activities such as team lunches, sports, karaoke, or occasional after-work gatherings. In addition to this, we will provide you with: Competitive salary + annual bonus Health insurance , Dental and Vision coverage (including spouse and family coverage) 401K Company match Life insurance Cell Phone & Internet reimbursement 25 days of PTO/year Commuter benefit Gym membership via ClassPass IT equipment allowance Professional development & trainings Team fun: regular company gatherings and team events As part of our recruitment process, we may carry out background checks in line with the applicable laws and regulations in the countries where we operate. These checks may include verification of employment history, education, and, where legally authorized, criminal records. Any background checks will be performed lawfully before formal employment contracts are signed, with the candidate’s consent, and all information collected will be handled confidentially. We may use artificial intelligence (AI) tools to assist with certain stages of the recruitment process. These tools are used to support our recruitment team and do not replace human decision-making. Final hiring decisions are always made by people. If you would like further information about how your data is processed, you can contact us at [email protected] .

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