Sr. Gen AI Engineer

BTI Solutions • Ridgefield Park, NJ

1d

About The Position

Sr. Gen AI Engineer 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 We are an outstanding national staffing company with 19 years of success Corporate Values 1. Guided by Integrity We earn trust by keeping our promises and holding ourselves and each other accountable to do the right thing in all circumstances 2. Strive for Excellence We strive to deliver quality candidates with efficiency and professionalism leading to the complete satisfaction of our clients 3. Stronger Together We embrace each other’s differences and practice collaborative communication to build strong partnerships and relationships to achieve successful outcomes 4. Think Big We continuously challenge ourselves and seek innovative ideas to improve and strengthen our company, clients, and partners for long-term success 5. Achieve Impact We commit ourselves to empowering and uplifting the people and communities we serve for a better tomorrow To be the foundation of all connections and the driver of new discoveries, growth, and transformation for our employees, candidates, clients, partners, and community Connecting talented employees and great companies to attain new experiences and opportunities to fulfill their needs and achieve their goals.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level