AI/ML Engineer

TechPossible

Denham Springs, LA

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JOB DETAILS

SALARY

SKILLS

Algorithms, Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Audio Streaming, Budgeting, Business Solutions, Business Strategy, Business Support, Cloud Computing, Code Reviews, Communication Skills, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Customer Satisfaction, Customer Support/Service, Data Sets, Database Design, Docker, GCP (Good Clinical Practices), Git, Health Insurance, Identify Issues, Industry/Trade Analysis, JSON, Machine Tool, Messaging Middleware, Microsoft SQL Server, Microsoft Windows Azure, Natural Language Processing (NLP), On Call, Performance Analysis, Performance Metrics, PostgreSQL, Problem Solving Skills, Production Control, Python Programming/Scripting Language, Quality Metrics, REST (Representational State Transfer), Regression Testing, Reimbursement, Risk, SIP (Session Initiation Protocol), SQL (Structured Query Language), Semantic Search, Software Engineering, Systems Administration/Management, Systems Maintenance, Team Player, Technical Support, Technical/Engineering Design, Testing, Time Management, Training/Teaching

LOCATION

Denham Springs, LA

POSTED

30+ days ago

Benefits:

401(k) matching
Health insurance
Opportunity for advancement
Paid time off
Training & development

TechPossible is seeking a motivated AI/ML Engineer to join our team! At TechPossible, you’ll work alongside a group of dedicated professionals who take pride in delivering high-quality IT and managed services. We support businesses in managing, securing, and maintaining their technology systems, and we do it with a strong commitment to honesty, integrity, and doing things the right way. If you’re passionate about building innovative solutions and want to make a meaningful impact, you’ll feel right at home here.

Job Summary: The AI/ML Engineer is the core hands-on builder on the AI team. This person writes the code that makes the AI features work — the voice agent prompts, the intent classifiers, the RAG pipelines, the evaluation harnesses, and the integrations that connect AI capabilities to business systems.

Essential Job Responsibilities: (Including but not limited to)

Implement AI workflows, including workflow logic, intent classification, entity extraction, and multi-step decision processes
Build and tune LLM-powered features using OpenAI, Anthropic, and other APIs — including prompt engineering, structured output parsing, and function calling
Develop NLP/classification systems for routing
Design and run model evaluations: build test sets, measure accuracy/latency/cost, iterate on prompts and model choices
Tune confidence thresholds (e.g., 90%/70% auto-vs-human routing) and monitor drift in production
Integrate AI and workflows with existing enterprise systems
Implement observability for AI systems, including structured logging, prompt and pipeline tracing, and cost attribution per execution
Collaborate with cross-functional teams to operationalize and iterate on prompts
Contribute to code review, technical design docs, and on-call rotations
Delivers responsive and professional customer support by diagnosing and resolving technical issues, communicating clearly with non-technical users, and ensuring timely follow-up to maintain high levels of customer satisfaction
Keep up with rapidly evolving technologies, algorithms, and industry trends
Work closely with business managers and other engineers to align AI strategies with company goals

Required Qualifications:

Strong experience and knowledge in Python and TypeScript
Hands-on LLM API experience: Anthropic Claude, OpenAI, at least one other provider; function calling, JSON mode, streaming
Prompt engineering as a systematic practice — not ad-hoc wordsmithing, but versioned prompts with test sets and regression checks
NLP fundamentals: intent classification, NER, embeddings, semantic search (pgvector, Pinecone)
Create evaluation approaches that define meaningful success metrics, build test datasets, and track performance against client-specific KPIs.
Model selection tradeoffs: when to use GPT-5 vs. Claude Sonnet vs. Haiku, when to fine-tune, when RAG is the right pattern

Voice AI

STT/TTS integration: Deepgram Nova/Aura, Whisper, ElevenLabs
Real-time streaming audio handling — latency budgets, interruption handling, turn-taking
Twilio Voice API, SIP trunking concepts, WebRTC awareness

Software Engineering

Backend development: REST APIs, async patterns, message queues
Databases: SQL (PostgreSQL, SQL Server), basic schema design; vector DB basics
Cloud: Azure (AWS/GCP acceptable), containerization (Docker)
Git, CI/CD, code review fundamentals

Preferred Skills: (Not Required)

MLOps tooling: Langfuse, MLflow, Weights & Biases
Familiarity with model adaptation techniques, such as fine-tuning (e.g., LoRA, supervised approaches)
Experience with frameworks: LangChain, LlamaIndex, Pydantic AI — used judiciously, not as a crutch

Benefits:

Health Insurance – TechPossible will pay 50% of the employee’s premium
401k Contribution – TechPossible will match employee contribution up to 3%
Optional benefits: Dental, Vision, Accident, Critical Illness, Short Term Disability, and Life Insurance.
Paid Time Off
Paid Holidays
Access to Employee Assistance Program
Company provided health club membership
Travel reimbursement
Opportunities for professional development and certification support
Supportive, team-oriented work environment

At TechPossible, we speak human, and we deliver results. We embed with your team to take full responsibility for your technology, bringing clarity where there’s complexity and control where there’s risk. Our experts secure, optimize, and manage your systems so they consistently perform at a high level. We don’t just keep things running; we make your technology a reliable driver of growth and a foundation for what’s next.

About the Company

TechPossible

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