Applied AI Engineer

Join to apply for the Applied AI Engineer role at Boam AI Get AI-powered advice on this job and more exclusive features. Ship production ML and agentic AI powering market leaders worldwide Boam AI builds managed data solutions that transform messy, unstructured signals from public, private, and proprietary sources into structured, reliable, and always up-to-date intelligence on millions of SMBs and enterprises worldwide. These agentic systems power CRMs, data warehouses, AI products, and mission‑critical decisions across the enterprise. As an Applied AI Engineer, you will own the lifecycle of the models and agents that power our product. You will build and maintain ML data pipelines, develop production‑ready LLM‑ and agent‑driven features, and work closely with backend engineers to integrate models into real systems. This is a role for someone who has shipped ML to production, wants real ownership over models and pipelines, and is excited to work on a small, senior team where AI is at the core of the product. What You’ll Do Own the ML model lifecycle from training and evaluation to deployment Build and maintain ML & agentic data pipelines for training, inference, and monitoring Develop production‑ready agentic and large‑language‑model–driven features Integrate models into production systems in close collaboration with backend engineers Implement experiment tracking, model CI/CD, and automated retraining Improve performance, reliability, and observability of ML and AI systems in production Work with product and data teams to turn ambiguous problems into concrete ML/AI solutions Use next‑gen AI tools to improve iteration speed and model quality You Might Be a Fit If... 3+ years of ML engineering experience working on production systems Strong Python skills and hands‑on ownership of end‑to‑end ML pipelines or agentic systems Comfortable with data preprocessing, feature engineering, and evaluation at scale Familiarity with LLMs or modern foundation models Experience with common ML tooling (e.g. PyTorch, TensorFlow, XGBoost, vector DBs, experiment trackers) Comfortable working across APIs, data stores, and infrastructure, not just notebooks Bias to ship, measure, and refine rather than chase perfect offline metrics Motivated by solving real customer problems and seeing models used in the wild Thrive without heavy process, QA buffers, or endless safeguards – you own what you ship Why Boam AI Join a no‑politics, high‑trust, low‑ego, and high‑talent team Work on mission‑critical ML/AI systems used by top‑tier enterprise customers Work directly with founders, the Head of Engineering, and senior engineers on problems that matter High autonomy, real impact, and clear ownership from day one Operate at the intersection of AI, data infrastructure, and enterprise workflows Top‑tier compensation with meaningful equity upside Help shape the ML/AI platform, patterns, and practices you can be proud of Our Hiring Process Intro Call: A short conversation to learn more about you, share context on Boam AI and the ML/AI role, and answer initial questions. Deep Dive: Walk us through past ML/AI work, systems you have built, and how you think about complex, ambiguous modeling and production challenges. Work Sample: Solve a real Boam‑style ML/AI challenge that shows your modeling approach, pipeline thinking, and execution muscle. Founder / Leadership Conversation: Candid discussion with our founder and Head of Engineering on ambition, values, ownership, and how you would help us scale our ML and agentic systems. Apply between Dec 15, 2025 and Jan 10, 2026. After Jan 10, we’ll review all applications and quickly invite the candidates we’d like to take forward. Seniority level Mid‑Senior level Employment type Full‑time Job function Engineering and Information Technology Industries Technology, Information and Internet #J-18808-Ljbffr