AI Engineer
Job in
Addison, Dallas County, Texas, 75001, USA
Listed on 2026-06-01
Listing for:
Confie
Full Time
position Listed on 2026-06-01
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
- $110000 - $140000 / year
- Comprehensive benefits package including medical, dental, vision, and life insurance
- Performance-based bonuses to reward your contributions*
- Paid time off to recharge and maintain a healthy work-life balance
- Flexible work options, including remote and hybrid opportunities, if eligible
- Retirement Plan (401k) with company-matched contributions
- Education Advancement, for employees and qualified dependents, via the Confie Enablement Scholarship Fund
- Fitness Reimbursement - up to $15/month for gym memberships
- Inclusive workplace through a strong commitment to Diversity, Equity, and Inclusion
- Employee Assistance Program - confidential support for personal or professional challenges, at no cost
- Extra Perks - optional plans for disability, hospital indemnity, health advocate program, universal life, critical illness, accident insurance, and even pet insurance
Responsible for designing, developing, and deploying production-grade AI solutions including autonomous agents, generative AI applications, and RAG-based systems. You will leverage large language models (LLMs), agentic frameworks, and advanced machine learning techniques to automate workflows, improve customer experiences, and drive business innovation.
Essential Duties & Responsibilities
Design and deploy autonomous AI agents using frameworks like Lang Graph, Auto Gen, CrewAI, or OpenAI Assistants API for multi-step reasoning and task execution.
Implement function calling, tool use, and API integrations enabling LLMs to interact with enterprise systems, databases, and external applications.
Design agent memory systems including conversational memory, long-term knowledge retention, and context management strategies.
Build advanced RAG systems with vector databases, hybrid search (dense + sparse retrieval), and reranking for domain-specific chatbots and knowledge retrieval.
Develop generative AI solutions for text generation, summarization, audio-to-text transcription, and call center conversation insights using LLMs.
Develop advanced prompting strategies including chain-of-thought reasoning, few-shot learning, and structured output generation.
Integrate with AI platforms including Snowflake Cortex, OpenAI, Azure AI Studio, AWS Bedrock, and Anthropic Claude.
Implement AI observability, guardrails, and evaluation frameworks (RAGAs, Tru Lens, Deep Eval) to ensure quality, safety, and reliability.
Conduct experiments and fine-tune models using techniques like LoRA and QLoRA to optimize performance for domain-specific use cases.
Deploy production solutions using containerization (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.
Continuously monitor the performance of AI solutions and implement improvements.
Create high-level and detailed design documentation for AI solutions, including architecture diagrams and technology selection rationale.
Collaborate with cross-functional teams to identify and prioritize high-impact AI opportunities that drive significant business value.
Mentor and provide guidance to junior team members; participate in code reviews and maintain high-quality engineering standards.
Keep updated with advances in AI technology and find opportunities to upgrade existing solutions.
Adhere to best practices in data privacy and security when working with sensitive data.
Qualifications and Education Requirements
Minimum of 3 years of professional experience in AI engineering or related roles.
3+ years experience developing AI/ML solutions on platforms such as Snowflake, Azure, AWS , OpenAI, Databricks, or similar.
2+ years hands-on experience with Generative AI including LLM application development, RAG systems, and production deployments.
Experience with agentic AI frameworks (Lang Graph, Auto Gen, CrewAI, OpenAI Assistants API) and multi-agent orchestration.
Proficiency in Python, Lang Chain/Llama Index, and vector databases (Pinecone, Weaviate, Chroma, pgvector, Snowflake).
Expertise in prompt engineering including chain-of-thought, few-shot learning, and structured outputs (JSON mode, function calling).
Experience with evaluation frameworks for Generative AI (RAGAs, Tru Lens, Deep Eval) in the context of text generation.
Understanding of AI safety concepts including guardrails, content filtering, hallucination mitigation, and red-teaming.
Experience with data preprocessing, feature engineering, and model evaluation techniques.
Solid understanding of software engineering principles and best practices.
Experience bringing GenAI projects through production and implementation with measurable business impact.
Soft Skills
Strong analytical and problem-solving skills.
Excellent communication skills with ability to articulate complex technical concepts to both technical and non-technical stakeholders.
Highly motivated and self-driven with ability to work independently and in collaborative team environments.
Ability to think creatively about applying AI to solve business problems.
Effective time management and…
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