Agentic AI Engineer

Das ist der Job

Hands‑on experience with AWS AI/ML services – Bedrock, Strands, AgentCore, SageMaker, or equivalent agentic frameworks.

Darum lohnt es sich

Write well‑designed, well‑tested, and maintainable code; participate in code reviews to maintain quality and distribute AI/ML knowledge across the team. Collaborate cross‑functionally with engineers, data teams, and compliance stakeholders to ensure AI outputs meet accuracy and regulatory standards.

Curiosity‑driven – you stay current with fast‑moving AI research and tooling and bring new ideas to the team. Certain roles may be eligible for incentive compensation, equity, and benefits. Benefits & Perks Competitive cash compensation (based on experience). Competitive benefits package.

Modern 401(k) plan that includes access to crypto, financial wellness benefits, low fees and more. Monday team lunches, snacks and drinks. Fertility Benefit.

Opportunity for Impact TaxBit is seeking an Agentic AI Engineer excited by the intersection of AI and FinTech – building intelligent, customer‑facing products that redefine how users interact with tax and compliance workflows.

You’ll be at the forefront of applied AI, designing and shipping agentic systems that operate autonomously, reason across complex data, and deliver world‑class experiences to TaxBit’s enterprise customers.

Role and Responsibilities Design, build, and deploy customer‑facing agentic AI products using AWS‑native technologies including Strands Agents, AgentCore, Bedrock, and Lambda. Architect multi‑agent systems with reliable tool use, memory, and orchestration patterns that perform accurately in high‑stakes financial contexts.

Partner with product managers and customer success to deeply understand user problems and translate them into elegant, production‑grade AI solutions. Own the full lifecycle of AI features – from prompt engineering and agent design through evaluation, deployment, and monitoring.

Instrument and monitor agentic systems in production using observability tooling; iterate rapidly based on real user behavior and feedback. Professional Qualifications 3+ years of professional software engineering experience, with at least 1 year building and shipping AI/LLM‑powered applications in production.

Strong understanding of agentic patterns: tool use, RAG, memory management, multi‑agent orchestration, and human‑in‑the‑loop design. Experience designing and evaluating LLM pipelines including prompt engineering, output validation, and hallucination mitigation. Familiarity with AI observability, evaluation frameworks, and responsible AI practices.

Ability to work in an agile environment and communicate complex AI concepts clearly to both technical and non‑technical audiences. Bachelor’s degree in Computer Science, Machine Learning, relevant technical field, or equivalent practical experience.

Personal Characteristics Strong coding skills in Python and/or TypeScript; comfort working across the stack as needed. Experience with AWS cloud infrastructure, IAM, Lambda, and related services; DataDog and GitHub CI/CD a plus. High ownership mentality – you care about what happens after the code ships.

Passion for building AI systems that are not just capable, but trustworthy and reliable in a compliance‑sensitive environment. Compensation The base salary range for this role is $130,000 – $170,000.

Actual compensation will vary depending on various job‑related factors, including, but not limited to location, experience, level, and job qualifications. Equity (RSUs). Hybrid working model: 3 days in‑office, 2 days WFH/flexible. Discretionary Time Off – enjoy the flexibility to rest, refuel, and recharge.

Paid parental leave to bond with your child. Autonomous work and flexibility in how work is performed. #J-18808-Ljbffr