Company Description
On-Site
1yr contract
$10950/month
Job Description
About the Role
We are seeking a
Senior Generative AI Engineer
to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure.
You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value.
Job Description:
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
Qualifications
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
Additional Information
All your information will be kept confidential according to EEO guidelines.