POSITION SUMMARY:
We are seeking an Sr AI Engineer to join our Information Technology team at our corporate office in Springfield, MO.
The Sr AI Engineer serves as a senior technical leader responsible for architecting, scaling, and governing enterprise AI platforms and solutions aligned with the enterprise AI roadmap. This role leads the design and operationalization of advanced AI systems, including generative AI, agentic workflows, retrieval-augmented generation (RAG), and intelligent automation capabilities that drive measurable business impact across the enterprise.
This position provides technical leadership across AI engineering initiatives, establishes enterprise AI standards and best practices, mentors engineering teams, and partners closely with business, data, security, and platform leaders to ensure scalable, secure, and production-ready AI ecosystems.
This position requires working onsite in our Springfield, MO headquarters.
ESSENTIAL FUNCTIONS:
- Lead enterprise AI architecture decisions, reference patterns, and platform strategies across multiple business domains.
- Collaborate with stakeholders to identify AI-driven automation and insight opportunities and define success metrics/acceptance criteria.
- Translate business needs into technical requirements and design end-to-end AI workflows, including data sourcing, orchestration, and integration points.
- Ensure data readiness by assessing availability and quality across enterprise and third-party sources; partner with Data Engineering to design and validate pipelines that produce high-quality, AI-ready datasets with data contracts, lineage, and schema-drift detection.
- Perform data preparation and transformation in SQL or Python when needed for AI workflows.
- Conduct data quality assessments, establish validation rules, maintain data lineage and data contracts, and implement schema-drift detection with automated gates.
- Design, develop, and deploy LLM-based, RAG, agentic AI, and generative AI solutions using modern ML/LLM frameworks and cloud AI services.
- Contribute to and implement enterprise PromptOps and LLMOps practices including evaluation pipelines, prompt governance, structured outputs, guardrails, rollback strategies, and automated testing.
- Build and operate autonomous and semi-autonomous AI workflows with auditable actions, human-in-the-loop approvals, feature flags, and operational safeguards.
- Implement model lifecycle management with experiment tracking, model registry, retraining, embedding/vector-index versioning, rollback, and monitoring.
- Lead evaluation and selection of foundation models, embedding strategies, vector retrieval architectures, and inference optimization techniques.
- Integrate AI solutions via APIs and event-driven architectures using versioned, backward-compatible contracts with semantic versioning and deprecation policies.
- Apply MLOps and LLMOps best practices for scalable, observable, and secure deployments including containerization, orchestration, CI/CD, and model lifecycle management.
- Implement automated testing including unit, integration, regression, evaluation, and contract testing for AI systems and services.
- Partner with Data Scientists and engineering teams to productionize AI and ML solutions into scalable enterprise systems.
- Provide technical mentorship and code/design reviews for AI Engineers, Data Engineers, and software development teams.
- Ensure responsible AI governance including RBAC/IAM, secrets management, PII minimization/redaction, audit logging, explainability, and compliance with governance and privacy standards.
- Lead implementation of observability frameworks including tracing, telemetry, hallucination detection, token/cost monitoring, dashboards, and alerting.
- Establish service-level objectives (SLOs), operational standards, reliability metrics, and incident response processes for AI platforms.
- Research and evaluate emerging AI technologies such as multimodal models, vector databases, agentic AI, and AI infrastructure platforms.
- Contribute to AI standards, reusable frameworks, engineering documentation, and enterprise best practices.
- Participate in on-call rotation and operational support activities as needed.
- ALL OTHER DUTIES AS ASSIGNED
EXPERIENCE/QUALIFICATIONS:
- Minimum Degree Required: Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (or equivalent experience).
- 5+ years of experience in AI engineering, machine learning systems, distributed systems, or enterprise AI platform development.
- 3+ years designing and deploying enterprise-scale LLM, RAG, or agentic AI solutions in production environments.
- Demonstrated experience leading architecture and delivery of scalable AI platforms or mission-critical AI systems.
- Deep proficiency in Python and modern AI/ML frameworks.
- Experience deploying LLM/RAG systems with enterprise data including evaluation frameworks, guardrails, and structured-output validation.
- Strong experience with vector databases, semantic retrieval systems, and embedding optimization strategies.
- Solid understanding of SQL, data modeling, and data preparation for AI consumption.
- Experience with major cloud platforms (AWS, Azure, GCP) and enterprise data platforms/warehouses such as Snowflake.
- Experience with API development, containerization, orchestration platforms such as Kubernetes, and CI/CD automation.
- Strong understanding of AI governance, security, compliance, and responsible AI practices.
- Experience mentoring engineers and leading cross-functional technical initiatives.
KNOWLEDGE, SKILLS, AND ABILITY:
- Strong systems architecture and platform engineering expertise.
- Ability to lead technical strategy and influence architectural direction across teams.
- Strong analytical and problem-solving skills with an end-to-end ownership mindset.
- Ability to translate complex AI concepts into actionable business outcomes.
- Excellent communication and collaboration skills across technical and business teams.
- Expertise in designing scalable, resilient, and maintainable AI systems.
- Proficiency with Git-based version control and collaborative development workflows.
- Familiarity with Agile methodologies and iterative delivery models.
- Understanding of AI feasibility, ROI, and value realization within enterprise environments.
- Experience mentoring engineers and fostering engineering best practices.
- Commitment to responsible and ethical AI development aligned with company standards.
TRAVEL REQUIREMENTS:
PHYSICAL REQUIREMENTS:
Regularly sits and works on a computer.
Occasionally stands and walks.
Seldom/never lifts up to 50 lbs.
INDEPENDENT JUDGEMENT:
Performs duties within scope of general company policies, procedures, and objectives. Analyzes problems and performs needs assessments. Uses judgment in adapting broad guidelines to achieve desired result. Regular exercise of independent judgment within accepted practices. Makes recommendations that affect policies, procedures, and practices.
Full Time Benefits Summary:
Enjoy discounts on retail merchandise, our restaurants, world-class resorts and conservation attractions!
- Medical
- Dental
- Vision
- Health Savings Account
- Flexible Spending Account
- Voluntary benefits
- 401k Retirement Savings
- Paid holidays
- Paid vacation
- Paid sick time
- Bass Pro Cares Fund
- And more!
Bass Pro Shops is an equal opportunity employer. Hiring decisions are administered without regard to race, color, creed, religion, sex, pregnancy, sexual orientation, gender identity, age, national origin, ancestry, citizenship status, disability, veteran status, genetic information, or any other basis protected by applicable federal, state or local law.
Reasonable Accommodations
Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.
If you need a reasonable accommodation for any part of the application process, please visit your nearest location or contact us at hrcompliance@basspro.com.
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