Senior AI Solutions Developer AI CoE

Acunor Inc; Rutherford (NJ); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Acunor Inc in Rutherford, NJ is seeking a Senior AI Solutions Developer to lead hands-on AI-enabled applications and integrations within the AI CoE. You will work with business teams to turn complex workflows into practical prototypes and scalable solutions.

The role emphasizes Python, APIs, data integration, and LLM-based tooling, with an focus on governance, security, and enterprise patterns in a hybrid in-office setting.

Qualifications

• Bachelor's degree or equivalent in CS/engineering or related field.
• 5–8 years in software development or related roles.
• Strong Python and API integration experience.
• Experience with AI-enabled applications and LLM tools.
• Experience collaborating with business stakeholders and end users.
• Understanding enterprise security, data access, and governance.

Responsibilities

• Prototype and develop AI-enabled workflows, assistants, and automations.
• Integrate with enterprise systems while following security and standards.
• Collaborate with business teams and domain experts to translate needs into solutions.
• Apply governance, risk, and CoE enablement considerations.
• Support scalable delivery by partnering with architecture, data, and security teams.

Skills

Python

APIs

System integration

SQL

AI-enabled applications

Stakeholder collaboration

Security & governance

Observability

Agile mindset

Education

Bachelor's degree or equivalent

Tools

FastMCP

LangGraph

LangSmith

Weights & Biases

OpenTelemetry

Job description

Job Title: Senior AI Solutions Developer, AI CoE

Location: Rutherford, NJ (hybrid; three days in office per week)

Client: Retail domain

Who You Are

• You are a hands-on developer with strong experience building AI-enabled applications, assistants, workflows, and integrations. You have strong software engineering fundamentals, deep Python experience, and the ability to connect systems, data, APIs, and services into practical working solutions.
• You are comfortable working directly with business stakeholders, application teams, and domain experts. You can move from an ambiguous business problem to a working prototype by understanding the workflow, systems, data, exceptions, and operational constraints involved.
• You bring an agile mindset to an enterprise environment. You are comfortable building quickly, learning through prototypes, documenting what works, and helping shape repeatable patterns for a growing AI Center of Excellence. You understand that successful AI solutions require not only strong engineering, but also practical governance, risk, security, data access, evaluation, and adoption considerations.

What You'll Do

Prototype and Solution Development

• Work directly with business teams, application teams, and domain experts to understand workflows, pain points, systems, data, exceptions, and operational constraints.
• Build rapid prototypes and proof-of-concepts for AI-enabled workflows, assistants,agents, automations, and features in close partnership with users and stakeholders, testing ideas against real business processes and enterprise environments.
• Rapidly validate what is technically feasible, what is operationally useful, and what should not move forward.
• Translate prototype learnings into solution recommendations, technical patterns, implementation considerations, and governance inputs for the AI CoE.
• Help move successful prototypes toward scalable delivery by partnering with application, architecture, data, security, and platform teams.

Engineering and Integration

• Use Python, APIs, databases, and services to connect systems, data, documents, and workflows.
• Integrate with enterprise systems while following security, privacy, architecture, and technology standards.
• Work with authentication, authorization, secure data access, and permission aware integration patterns.
• Design solutions that are practical, maintainable, and appropriate for enterprise use.

AI Application Development

• Work with LLM-based tools and platforms to build applications that support business workflows.
• Implement orchestration approaches for multi-step workflows, tool usage, and agentic patterns.
• Apply retrieval, structured data access, and workflow automation where appropriate.
• Build AI-enabled workflows that include appropriate human review, guardrails, error handling, and escalation paths.

Governance, Risk, and CoE Enablement

• Support practical governance, risk, and compliance considerations based on lessons learned from AI prototypes and proof-of-concepts.
• Help identify common risks, controls, review points, and documentation needs for AI-enabled solutions.
• Partner with security, privacy, legal, data, architecture, and governance stakeholders to support responsible AI solution development.

You'll Need to Have

• Bachelor's degree or equivalent experience in Computer Science, Engineering, Information Systems, or a related field.
• 5 to 8 years of experience in software development, application development, systems engineering, or related engineering roles.
• Strong proficiency in Python.
• Strong experience with APIs, system integration, and service-based architectures.
• Solid knowledge of SQL and working with data in enterprise environments.
• Experience building AI-enabled applications, assistants, agents, automations, or workflows using modern LLM tools and platforms.
• Experience working directly with business stakeholders or end users to design, prototype, and iterate on software or AI-enabled solutions.
• Experience working with tool integration patterns, including exposing or consuming internal tools and services within application workflows.
• Understanding of orchestration approaches for multi-step workflows, tool usage, and agentic patterns.
• Experience implementing logging, testing, and basic observability.
• Understanding of authentication, authorization, secure data access, and enterprise integration considerations.
• Ability to identify practical risks, controls, dependencies, and trade-offs when developing AI-enabled solutions.
• Strong problem-solving skills and the ability to work through ambiguity.
• Strong written and verbal communication skills.
• Ability to manage multiple priorities in a fast-paced environment.

Key expectations:

• Experience in a forward-deployed engineering, solutions engineering, applied AI engineering, innovation lab, consulting engineering, or internal product/prototype development environment.
• Experience building or working with MCP servers, for example using FastMCP or similar tools.
• Experience with orchestration frameworks such as LangGraph or similar tools.
• Experience with evaluation and observability platforms such as LangSmith, Weights & Biases, or OpenTelemetry-based tracing.
• Experience with retrieval patterns and working with structured and unstructured data.
• Familiarity with enterprise AI governance considerations, including privacy, security, data access, HITL design, and responsible use.
• Experience working with security, privacy, legal, architecture, data governance, or risk stakeholders.