Agentic AI Developer

MACHINE LEARNING TECHNOLOGIES LLC; Atlanta (GA); On-site; USD 140,000 - 210,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC seeks an Agentic AI Developer to design and deliver AI-powered workflows within enterprise-scale environments. You will translate business needs into technical specs, build AI agent capabilities, and implement structured outputs with robust tool contracts and authorization controls.

You will collaborate on backend services, data processing, and evaluation datasets, ensuring security, governance, and reliable production deployments.

Qualifications

• Experience building AI-enabled applications for enterprise use
• Strong understanding of AI agent architectures and tool contracts
• Familiarity with data processing and governance
• Backend API development and integration

Responsibilities

• Partner with business users and SMEs to understand workflows, pain points, and outcomes.
• Translate requirements into technical specs, user stories, testable acceptance criteria, and delivery plans.
• Develop bounded AI capabilities for research, explanation, recommendation, and workflow assistance.
• Implement structured outputs, context retrieval, tool calling, prompt versioning, and output validation.
• Enforce authorization boundaries in code and tool permissions; evaluate model options against enterprise requirements.
• Build production-quality backend services, data processing components, and API integrations.
• Create unit, integration, and end-to-end tests; develop evaluation datasets with domain experts.
• Follow AI governance lifecycle, tooling paths, and release controls.
• Maintain traceability of decisions, prompts, documentation, and delivery records.
• Instrument application behavior, telemetry protections, cost attribution, and reliability measures.

Job description

Job Overview

• Job ID: J53661
• Job Title: Agentic AI Developer
• Location: Atlanta, GA
• Duration: 17 Months + Extension
• Domain Exposure: Government
• Work Authorization: US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD
• Client: To Be Discussed Later
• Employment Type: W-2, 1099, C2C

Job Description

Embedded Discovery and Solution Delivery: Partner directly with business users and subject‑matter experts to understand workflows, pain points, exceptions, and desired outcomes.

Translate business requirements into technical specifications, user stories, testable acceptance criteria, and incremental delivery plans.

Identify when deterministic logic, conventional automation, retrieval, or an AI agent is the appropriate solution.

Build working vertical slices that demonstrate business value rather than disconnected proofs of concept.

Communicate technical trade‑offs, risks, dependencies, and decisions clearly to technical and nontechnical stakeholders.

Agentic AI and LLM Application Engineering: Develop bounded AI capabilities for research, explanation, recommendation, and workflow assistance. Implement structured outputs, context retrieval, tool/function calling, prompt versioning, and output validation. Design tool contracts with explicit permissions, schemas, failure behavior, and audit requirements. Ground AI responses in approved, versioned sources and preserve links to supporting evidence. Implement human review, escalation, abstention, and fallback behavior.

Enforce authorization boundaries in application code and tool permissions—not through prompts alone. Evaluate model and framework options against approved enterprise requirements for quality, security, latency, and cost.

Software and Data Engineering: Build production‑quality backend services, APIs, data‑processing components, and workflow integrations. Develop Databricks notebooks/jobs and SQL transformations for ingestion, normalization, matching, comparison, and validation.

Implement data‑quality checks, schema validation, deduplication, reconciliation, and versioned processing rules. Maintain reproducibility through pinned rule sets, input references, and traceable execution records.

Collaborate on reviewer‑facing interfaces and end‑to‑end application behavior.

Engineer reliable integrations using appropriate retry, idempotency, timeout, and recovery patterns.

Quality, Evaluation, and Verification: Create unit, integration, end‑to‑end, regression, and negative tests. Develop representative evaluation datasets with domain experts. Assess AI outputs for grounding, correctness, usefulness, safety, and appropriate abstention. Test unauthorized tool use, prompt injection, sensitive‑data exposure, and failure scenarios. Trace delivered functionality and verification evidence to acceptance criteria. Review AI‑generated code with the same rigor as manually written code.

Security, Governance, and AI‑DLC: Follow the applicable AI‑DLC lifecycle, approved tooling paths, review requirements, and release controls.

Implement least‑privilege access, secure authentication, secrets management, and data‑access restrictions.

Use synthetic, mock, or approved de‑identified development data where required.

Maintain architecture decisions, prompt/tool documentation, approval evidence, and delivery records.

Escalate unresolved data classification, privacy, model approval, and risk decisions to accountable owners.

Preserve human authority over final business decisions and production promotion.

Operational Readiness: Instrument application behaviour, retrieval, tool calls, model usage, failures, and dependencies.

Establish prompt/model traceability and appropriate telemetry protections.

Implement usage and cost attribution, monitoring, s, and agreed reliability measures.

Produce deployment guidance, rollback procedures, runbooks, and support handover materials.

Work with platform and operations teams while retaining delivery‑team accountability for application quality and remediation.

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.