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Auxo Solutions

Sr. Engineer - Applied AI

Posted 4 Days Ago
Remote
Hiring Remotely in United States
155K-180K Annually
Senior level
Remote
Hiring Remotely in United States
155K-180K Annually
Senior level
The Applied AI Engineer will manage Ai/ML project lifecycles, build secure data pipelines, implement LLM solutions, and optimize AI models while collaborating with various teams.
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About Auxo Solutions - An Alpha Group Company


Built on top-level engineering and industry knowledge, Auxo Solutions, an Alpha Group company, delivers unmatched agility, creativity, and dedication to solve tomorrow’s problems today. Founded and operated by engineers, no one has a stronger foundation than our team.


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About the role


As an Applied AI Engineer at AlphaFMC, you will play a pivotal role in shaping how leading financial services organizations adopt and scale AI. You will work on high-visibility initiatives inside wealth management firms, banks, and insurance companies, where the stakes are high and the standards for performance, safety, and governance are non-negotiable.

Your experience in data science, LLMs, and agentic AI will directly influence how our clients operate and compete. You will have real ownership across the full solution lifecycle, with visibility into both technical delivery and business outcomes, and meaningful input into the AI strategies we bring to market.


What you'll do

  • Own the full lifecycle of AI/ML projects, including problem framing, data acquisition, feature engineering, model and LLM selection and fine-tuning, evaluation, deployment, monitoring, and continuous improvement.
  • Design, build, and maintain scalable data pipelines for ingestion, preprocessing, and feature engineering, supporting both structured and unstructured enterprise data.
  • Implement RAG pipelines using vector databases and embedding strategies to ground LLMs in proprietary enterprise data; fine-tune, prompt-engineer, and evaluate LLMs for domain-specific tasks; design and orchestrate agentic workflows including tool-using agents, multi-step planners, guardrails, and alignment mechanisms.
  • Establish robust evaluation frameworks covering hallucination checks, calibration, bias and fairness, and adversarial testing; build logging, telemetry, safeguards, governance artifacts, and documentation for model risk management.
  • Lead the end-to-end lifecycle of AI models from experimentation and prototyping to scalable deployment in production environments using MLOps best practices, CI/CD, and cloud platforms (AWS, Azure, GCP).
  • Optimize inference latency, throughput, and cost; establish monitoring and observability to ensure performance, safety, and reliability in mission-critical environments.
  • Work closely with AI engineers, software engineers, product managers, and business stakeholders to translate complex business problems into AI-native solutions with measurable impact.


Qualifications

  • A bachelors' degree in a related field and at least 5 years of experience designing and deploying production-grade AI/ML solutions, including at least one production LLM agent or agentic workflow
  • At least 5 years' experience working in Python and SQL, with hands-on experience in AI/ML frameworks such as scikit-learn, TensorFlow, or PyTorch
  • Proven experience with cloud-native development and data warehousing solutions (Snowflake, Azure Data Lake, AWS S3, or equivalent)
  • Strong knowledge of LLMs, transformers, NLP, agentic modeling, and reinforcement learning concepts
  • Experience with open and commercial LLMs, RAG pipelines, and agent frameworks (LangGraph, LangChain Agents, DSPy, or equivalent)
  • Experience building data ETL/ELT pipelines and deploying models using Docker/Kubernetes, CI/CD, and monitoring/observability tools
  • Familiarity with model risk management and trustworthy AI practices, especially in regulated industries
  • Strong analytical, problem-solving, and communication skills; comfortable working across technical teams and business stakeholders

How you know if you would be successful in this role

  • You demonstrate tenured experience across data science, LLMs, and agentic AI. You can move fluidly between model experimentation and production engineering, and you understand the tradeoffs between approaches.
  • You know how to establish and enforce evaluation frameworks to ensure production-ready deployment of AI/ML solutions, with particular sensitivity to the governance requirements of financial services and/or Insurance industries.
  • You work effectively with onshore and offshore engineers, product managers, and business stakeholders.
  • You can explain a RAG pipeline to a senior engineer and a hallucination risk to a compliance officer, adjusting your communication without dumbing things down.
  • You can employ modern AI/ML and GenAI design patterns to solve complex business problems and integrate advanced AI into application architectures with measurable impact.
  • You thrive in a fast-paced environment, stay current with a rapidly evolving AI landscape, and know when to adopt new tools and when to resist the hype.


Other Info

  • Benefits Offered: Medical, Dental, and & Vision Insurance. Life, Short Term Disability, and Long Term Disability Insurance. 25 days of accrued PTO, paid holidays. Profit Sharing-based annual target bonus. Company sponsored 401(k) plan with match. Monthly wellness and tech stipend.
  • This role is not eligible for sponsorship at this time.
  • This position may require up to 15% travel (to client sites).
  • The position requires the employee to be able to work 8:30am - 5:30pm EST Monday through Friday.
  • The successful candidate will be subject to thorough background checks, including physical location verifications.
  • No agencies, please.

Top Skills

AWS
Azure
Azure Data Lake
Docker
GCP
Kubernetes
Python
PyTorch
Scikit-Learn
Snowflake
SQL
TensorFlow

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