Sr. Gen AI Engineer
BTI SolutionsWhy work with us?
Proven people.
Everyone on our team has earned a CPC (Certified Personnel Consultant) or CTS (Certified Temporary Staffing Specialist) accreditation from the National Association of Personnel Services. We are experts at staffing and recruiting with more than 16 years of experience serving employers.
Proven process.
Our approach to staffing isn’t just a little bit different; it’s a whole different ball game. While most staffing firms emphasize transactional services (taking and filling job orders), BTI Solutions focuses on providing more strategic solutions.
By acting as workforce consultants, we are able to find innovative and intelligent strategies for improving productivity, meeting project deadlines, improving hiring quality, decreasing turnover, and reducing total labor costs.
Our recruiting and candidate assessment process assures the highest quality matches between job seeker and employer, so you will get people who not only have the right qualifications but who also have the appropriate personality fit for your organization.
Proven results.
More than anything, the biggest difference with BTI Solutions is the one that matters most: bottom-line results.
- 95% client satisfaction rate – measures client satisfaction vs. expectations.
- Our clients have worked with us for over 10 years, on average.
- BTI Solutions counts 4 Global Telecommunication companies as clients.
- Client referrals are BTI Solutions’ largest source of new clients.
- Google Review 4.4, Facebook Review 4.8
What You’ll Do
- Design and develop algorithms for generative models using deep learning techniques
- Design and build LLM-powered applications for internal and/or customer-facing use cases
- Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems
- Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration
- Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate
- Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability
- Implement prompt engineering, structured outputs, tool calling, and model optimization strategies
- Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices
- Build monitoring, observability, and feedback loops for model and application performance in production
- Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems
- Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities
- Mentor other engineers and contribute to architecture, technical direction, and engineering best practices
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field
- 5+ years of software engineering, machine/deep learning engineering, or applied AI experience
- 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production
- Strong programming skills in Python and experience with backend/API development
- Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design
- Experience in optimizing RAG pipelines using both structured and unstructured data
- Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
- Experience in generative AI techniques such as GANs, and VAEs
- Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search
- Experience with cloud platforms such as AWS, GCP, or Azure
- Experience with Docker, Kubernetes, CI/CD, and production deployment practices
- Strong understanding of software architecture, scalability, reliability, and distributed systems
- Experience building evaluation, testing, and monitoring for AI systems
- Strong communication skills and ability to work closely with technical and non-technical stakeholder
Preferred Qualifications
- Experience fine-tuning or adapting open-source LLMs
- Advanced knowledge of natural language processing for text generation tasks
- Experience with PyTorch, TensorFlow, JAX, or related ML frameworks
- Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar
- Experience building multi-agent systems or advanced orchestration workflows
- Experience with AI safety, guardrails, red-teaming, privacy, and governance
- Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems
- Experience in customer-facing or enterprise SaaS products
- Experience in semiconductor/manufacturing, retail and e-commerce sectors
What Success Looks Like
- Deliver production-ready GenAI features that improve user experience and business outcomes
- Build reliable and scalable AI systems with strong quality, latency, and cost performance
- Establish best practices for evaluation, observability, and responsible AI development
- Help define the company’s long-term Generative AI architecture and roadmap
Compensation & Benefits
- Opportunity to shape the company’s GenAI strategy and core platform
- Work on high-impact, real-world AI products with ownership from design to deployment
- Collaborative environment with strong technical autonomy and room for growth