Full Stack GenAI Engineer

Job Description :

Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG).

Fine-tune foundation models using domain-specific data.

Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).

Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.

Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.

Monitor and optimize model performance, latency, and cost.

Use techniques like quantization, distillation, and caching to improve efficiency.

Stay ahead of GenAI trends and emerging technologies.

Drive experimentation with new models, agents, and frameworks (e.g., LangChain, LlamaIndex, OpenAI, Anthropic, etc.).

Ensure compliance with data privacy, security, and regulatory standards.

Evaluate and select appropriate model types (open-source vs proprietary) based on business needs.

Lead hands-on solution evaluations, prototypes, and proofs of concept, especially for initiatives involving AI, GenAI, and emerging technologies

Make informed architectural trade-offs based on business needs, performance, cost, and long-term maintainability

Contribute reusable patterns and documentation that support solution delivery across teams

Stay informed on trends in cloud services, architecture frameworks, and GenAI tooling.

Full Stack 5 years Java / Python, CI / C pipelines must

Atleast 2 years should be with Gen AI tools and framework.

AWS - Must

10+ years of software engineering and development experience

Proven experience in building and deploying GenAI applications in production.

Strong programming skills in Python / JAVA and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face, etc.).

Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate).

Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).

Familiarity with CI / CD for ML workflows and versioning tools like MLflow or DVC.

Knowledge of prompt engineering, few-shot learning, and agent-based systems.

Hands-on experience designing and building cloud-native solutions (preferably on AWS)

Experience with modern architecture styles : microservices, APIs, event-driven systems

Strong ability to articulate technical solutions, trade-offs, and system behavior to both technical and non-technical stakeholders

Bonus if you have (Preferred) :

Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock)

Familiarity with AWS AI / ML services (e.g., SageMaker, Bedrock, Comprehend, Lex)

AWS AI certification

Financial Services experience

Pi-square technologies is a Michigan (USA) Headquartered Automotive Embedded Engineering Services company, Synergy Partner for major OEMs and Tier 1s and their implementation partners in Automotive Embedded Product Development, Projects, Requirements Analysis, Software Design, Software Implementation, Efficient Build, Release Process, and turnkey software V & V Services. We have more than 20+ years of industry expertise with specialization in the latest cutting-edge automotive technologies such as Infotainment, connected vehicles, Cyber security, OTA, and Advanced Safety / Body electronics.