Sedric

Description You'll design the architecture that lets AI run compliance at scale. Sedric is the AI compliance platform for financial services. Our agentic AI automates oversight across customer communications and marketing — real-time guardrails on calls, pre-approval review on every marketing asset, and post-publication monitoring across partners and channels. Because every customer gets a dedicated compliance model, accuracy goes up, false positives go down, and compliance teams move faster without taking on more risk. AI isn’t a feature at Sedric — it’s the product. Every agent, LLM flow, and retrieval pipeline that runs a customer’s compliance program runs on backend systems someone has to design, build, and keep fast, accurate, and cost-efficient at scale. We’re looking for a hands-on AI engineer who designs those systems and writes the code. You’ll own the architecture of our AI backend end to end, ship it to production, monitor how it performs with real customers, and raise the bar for the engineers around you through code reviews, design reviews, and mentoring. The mission? We're at an inflection point. Enterprise financial services clients are signing on, and they need more than a product — they need a platform. That means a unified LLM strategy, an architecture that scales, and an R&D org that moves with the same urgency as the business. This role reports to the AI team Dev Team Lead and is based in Tel Aviv (hybrid model). This is a hands-on engineering role. It’s not a research position and not a people-management role. You’ll spend most of your time designing and building production systems. What You’ll Own You'll own Sedric's AI reference architecture end to end — the patterns, standards, and platform capabilities that every AI initiative across engineering builds on. You'll lead architecture reviews, set the technology roadmap, and make the call on what we adopt, pilot, or retire. • Design and build the backend architecture for Sedric’s AI agents, LLM pipelines, and retrieval systems, and write a large share of the production code yourself • Take AI capabilities from prototype to production in a multi-tenant SaaS environment • Optimize for scale and cost: model selection, prompt and token efficiency, caching, batching, latency, and infrastructure spend • Build monitoring and evaluation for AI quality in production (accuracy, false positives, drift, cost per customer) and act on what it shows • Set engineering standards for AI development and mentor engineers through pairing, code reviews, and design reviews • Bring new AI techniques into the product when they solve a real customer problem, and prove it in production Requirements You're a fit if… • You have 5+ years of ML/AI architecture experience in a SaaS company • 3+ Backend development experience • You bring both the technical depth and the leadership range this role demands. • You've built agentic systems with tool use, planning, and multi-step reasoning in production, not just in a notebook • You've set up AI governance and evaluation harnesses from scratch • You have proven, hands-on experience with AI in production systems • You can take a project from concept to shipped and interface with stakeholders the whole way • You hold a relevant degree; an advanced degree in CS, ML, Statistics, or a related field is a plus • You're comfortable in front of customers and executives, translating technical tradeoffs into business terms You're probably not a fit if… • You want to execute against someone else's architecture, not design your own • You'd rather avoid customer or stakeholder conversations than lead them • You think about the technology and skip the business context it lives in • You need long runway before shipping — this role moves fast and mixes design with execution • You want a playbook handed to you rather than writing the first one What Success Looks Like Your first 90 days goals: • Day 30 — You understand the AI architecture of the platform end to end — the systems, the constraints, the decisions already made. • Day 60 — You've shipped LLM-driven improvements and optimized existing flows for latency and reliability. • Day 90 — You own AI design across the platform — teams come to you before they build, not after. Compensation & Benefits • Competitive salary aligned with industry standards • Meaningful equity in a high-growth compliance AI company • Direct access to leadership — no bureaucracy between you and impact • Flexible, output-first culture — we care what you ship, not when you log on • Work on problems that matter in an industry that’s ready to change How to Apply & Important Notice Do you think that this is for you? apply directly or send your resume to [email protected]. Equal Opportunity Employment Sedric.Ai is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or protected veteran status. AI & Recording Disclosure: To streamline our hiring process and ensure a thorough review, Sedric.Ai utilizes AI-powered tools to evaluate resumes, and our interviews may be recorded or assisted by an AI note-taker. By submitting your application, you acknowledge and consent to the use of these technologies during the recruitment process. If you prefer to opt out of AI resume screening or interview recordings, please notify our recruiting team at [Insert Contact Email/Link] to request a manual review or unrecorded interview.

Description Sedric is the AI compliance platform for financial services. Our agentic AI automates oversight across customer communications and marketing — real-time guardrails on calls, pre-approval review on every marketing asset, and post-publication monitoring across partners and channels. Because every customer gets a dedicated compliance model, accuracy goes up, false positives go down, and compliance teams move faster without taking on more risk. Our data lives in silos — Postgres, Snowflake, product usage, customer interactions, billing, infrastructure costs. Each one tells part of the story. Nobody sees the whole picture. When leadership asks “why did our cloud costs jump 30%?” or “which customers are actually driving growth?”, we spend days stitching together an answer that should take an hour. That gap slows down the decisions that matter most. We’re hiring our first Data Lead to close it. This is an engineer who thinks like an operator: you’ll build the foundation — architecture, pipelines, models — and then use it to connect product behavior, customer outcomes and business performance into one view that drives strategy. No inherited warehouse, no dashboard graveyard, no analyst backlog. A blank page, and a company that needs you to fill it. The Data Lead reports to our Head of Product, is based in Tel Aviv (hybrid), and works daily with Product, Engineering, Operations (GTM) and Finance. What You’ll Own The full data lifecycle — from raw data and modeling to insight, recommendation and measurable impact. You build the infrastructure, but the job is the decisions it enables. You go from data to analysis to action, and you own the outcome. • Data architecture — design and evolve the stack connecting Postgres, Snowflake, product usage, customer interaction, billing and infrastructure cost data into one source of truth • Pipelines and models — build and maintain production-grade ETL pipelines and clean, reusable data models in Snowflake and dbt • Data quality — set up checks and monitoring so nobody has to wonder whether a number is right • Product KPIs — define the metrics that matter across product, operations and the business, with one shared definition per metric • Strategic analysis — connect product usage, customer behavior, revenue and costs to answer the questions leadership is actually asking: where we grow, where we leak margin, what to build next • Product enablement — give Product the usage, adoption and retention insight it needs to prioritize, and make our own AI measurable: model accuracy, false positives, customer outcomes • Business operations enablement — give GTM and Finance self-serve dashboards, alerting and analysis on pipeline, revenue, unit economics and cloud costs • Impact — turn findings into initiatives with Product, Operations, Engineering and Finance, then measure whether they worked • AI-driven execution — use AI tools to write, review and debug SQL and dbt faster, so your time goes into judgment, not boilerplate Requirements You’re a fit if… You bring a data engineer’s foundation, an analyst’s business instinct, and the judgment to know when a simple query beats a sophisticated pipeline. • You have 5+ years of hands-on experience in data engineering or analytics engineering, with real exposure to business analytics • Your SQL is strong — this is a must — and you have deep experience with relational databases • You’ve built production-grade ETL pipelines and data models, not one-off scripts — ideally on Snowflake and dbt, with Python where it’s needed • You’ve built BI dashboards (Looker, Tableau, Omni or similar) and defined KPIs people actually trust • You connect the dots across domains — product usage to revenue, customer behavior to cost — and turn to an ambiguous question like “why did costs go up?” into a validated answer and a recommendation • You explain complex analysis clearly to engineers and executives, and you use it to move decisions, not just inform them • You’re skeptical of numbers that don’t add up, and won’t ship a dashboard you don’t trust yourself • You’ve been the first or only data person somewhere before, or you’re ready to be • Bonus: experience with product analytics or customer interaction data (calls, chats, messages), early-stage high-growth startups, or AI-driven products You’re probably not a fit if… • You want a fully built warehouse and a backlog of tickets waiting for you • You’d rather build the perfect pipeline than answer the business question in front of you • You’re a pure analyst who hands off the moment data needs engineering — or a pure engineer who stops at the pipeline • You need someone else to tell you which metrics matter • You see BI as a reporting function, not a decision-making one • You’re uncomfortable being the only data person in the room What Success Looks Like Day 30 — Mapped every data source across product, customer interactions, billing and infrastructure, and shipped a data quality audit flagging the biggest gaps and inconsistencies. Day 60 — Shipped the core data models and the first set of high-value product and business dashboards, with KPI definitions every team has signed off on. Day 90 — Delivered a data roadmap, moved at least one core metric from disputed to trusted, and brought leadership a data-driven recommendation that changed a decision. Compensation & Benefits • Competitive salary aligned with industry standards • Meaningful equity in a high-growth compliance AI company • Direct access to leadership — no bureaucracy between you and impact • Flexible, output-first culture — we care what you ship, not when you log on • Work on problems that matter in an industry that’s ready to change How to Apply & Important Notice Do you think that this is for you? apply directly or send your resume to [email protected] Equal Opportunity Employment Sedric.Ai is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or protected veteran status. AI & Recording Disclosure: To streamline our hiring process and ensure a thorough review, Sedric.Ai utilizes AI-powered tools to evaluate resumes, and our interviews may be recorded or assisted by an AI note-taker. By submitting your application, you acknowledge and consent to the use of these technologies during the recruitment process. If you prefer to opt out of AI resume screening or interview recordings, please notify our recruiting team at [Insert Contact Email/Link] to request a manual review or unrecorded interview.