Applied AI Engineer

Akaasa Technologies; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Akaasa Technologies seeks an experienced Applied AI Engineer in New York, NY to build a new enterprise-grade AI platform for Lending. This hands-on role requires deep ML expertise, production readiness, and the ability to lead AI initiatives from concept to deployment.

You will architect, implement, and continuously improve AI workflows, document extraction, and agentic systems while collaborating with technical and business stakeholders to deliver scalable, reliable AI solutions.

Qualifications

• Strong foundation in ML/AI with solid mathematical and analytical skills.
• Hands-on Python experience.
• Experience with PyTorch and LangChain frameworks.
• Production RAG experience is mandatory.
• Agentic AI workflows and multi-step AI systems experience.
• LLMOps and production AI systems experience.
• Ability to architect AI solutions and delivery plans.
• Knowledge of model evaluation, reliability, and monitoring.

Responsibilities

• Architect and implement an enterprise-grade AI platform for Lending.
• Define AI workflows, document extraction, and model enhancements.
• Build and operate production AI systems with monitoring.
• Collaborate with technical and business stakeholders to align requirements.
• Translate ambiguous AI problems into concrete architecture and plans.

Skills

Machine Learning

Python

RAG

Agentic AI

LLMOps

Production AI

Model evaluation

Architecting AI

Tools

PyTorch

LangChain

Job description

Applied AI Engineer
Location: New York, NY (Hybrid 4 5 days onsite)
Duration: 12 months
Interview Process: 1st Round Zoom | 2nd Round In-Person

Note:

• Must be local with DL copy
• LinkedIn with location (before 2022)
• Recent or recent second project must be at the current location

Ideal Candidate

The ideal candidate is an Applied AI SME and practitioner who can walk into a greenfield environment and confidently say:

"This is how the solution should be built, these are the capabilities we need, these are the challenges we need to address, and this is how I would deliver it."

They should be comfortable working directly with technical and business stakeholders and be capable of architecting, building, evaluating, and improving AI systems themselves.

Key distinction:

We are looking for someone who has applied AI-not simply someone who uses AI. Candidates whose experience is primarily traditional software development with AI APIs/LLMs layered on top will not be a strong fit.

Job Description

Client is seeking a highly experienced Applied AI Engineer / AI SME to help build a new enterprise-grade AI platform supporting the Lending business.

This is a hands-on Applied AI role for a practitioner with a strong foundation in Machine Learning, Python, document intelligence, RAG, Agentic AI, and LLMOps. The ideal candidate is not a software developer who has simply learned how to use AI models. We are looking for someone with strong core ML and mathematical knowledge who has applied AI to real-world, production systems.

The AI platform is being built from scratch, so this person will be expected to act as a technical SME, bring their own expertise and recommendations, and help define how AI workflows, document extraction, model enhancement, and agentic systems should be designed and implemented.

Required Skills

• Strong background in Machine Learning / Artificial Intelligence with solid mathematical and analytical fundamentals.
• Strong hands-on Python experience.
• Experience with PyTorch and modern AI/GenAI frameworks such as LangChain.
• Strong experience with document extraction/document intelligence and improving extraction quality.
• Production RAG experience is mandatory.
• Strong hands-on experience building Agentic AI workflows and orchestrating multi-step AI systems.
• Experience with LLMOps and operating LLM/GenAI systems in production.
• Demonstrated experience building and supporting live production AI systems, not just prototypes or personal projects.
• Ability to take an ambiguous AI problem and independently determine the architecture, approach, required resources, and delivery plan.
• Strong understanding of AI model evaluation, reliability, scalability, and monitoring.

Qualifications

• Financial Services experience is a major plus.
• Experience with Fixed Income, Institutional Lending, Capital Markets, or related domains.
• Experience working in regulated environments with strong audit, controls, security, and governance requirements.
• Familiarity with enterprise data governance and entitlement models.
• Experience designing reusable internal AI platforms or shared developer tooling.
• Full-stack engineering experience is beneficial.
• Frontend experience with React or Angular is a plus.