Experience
7 - 9 yrs
Job Location
Pune, India
Vacancy
1
Designation
Artificial Intelligence Developer
Job Type
ONSITE
Job Description
">AI Developer
7-9 Years Pune
- AI
Job Summary 2- Senior AI Developer
We are looking for a highly skilled Senior AI Developer to design, develop, and deploy AI solutions leveraging Edge LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), and LLM integrations. The ideal candidate will have experience building production-ready GenAI applications and an understanding of Functional Safety Engineering and DFMEA practices for developing reliable and robust AI-enabled systems.
Key Responsibilities
- Develop and deploy Edge LLM-based applications optimized for performance, latency, and resource-constrained environments.
- Design and implement advanced Prompt Engineering strategies to improve LLM response quality, accuracy, and consistency.
- Build and maintain RAG pipelines using vector databases, embeddings, and enterprise knowledge sources.
- Integrate LLMs with existing applications, products, APIs, and enterprise systems.
- Develop scalable AI services and microservices using Python and modern AI frameworks.
- Collaborate with cross-functional teams to gather requirements and translate business needs into AI-powered solutions.
- Apply Functional Safety Engineering principles during the development lifecycle to ensure system reliability and compliance.
- Participate in DFMEA activities to identify potential failure modes, assess risks, and implement mitigation strategies.
- Conduct model evaluation, testing, monitoring, and performance optimization for deployed AI solutions.
- Document AI architectures, workflows, and technical specifications.
Required Skills
- 7+ years of software development experience with at least 3-4 years in AI/ML or Generative AI development.
- Strong experience with Edge LLMs, LLM deployment, and inference optimization.
- Hands-on expertise in Prompt Engineering, RAG, LangChain, LlamaIndex, and vector databases.
- Experience integrating LLMs such as Llama, Gemma, Mistral, GPT, or similar foundation models.
- Proficiency in Python and AI/ML frameworks such as PyTorch or TensorFlow.
- Experience building and consuming REST APIs and integrating AI solutions into enterprise applications.
- Understanding of Functional Safety Engineering concepts and risk assessment methodologies.
- Knowledge of DFMEA processes and failure analysis techniques.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization technologies.
Preferred Qualifications
- Experience in Automotive, Industrial Automation, Robotics, Embedded Systems, or other safety-critical domains.
- Knowledge of MLOps, CI/CD pipelines, model monitoring, and AI governance.
- Experience with edge computing platforms and embedded AI deployments.
- Understanding of AI explainability, validation, and testing methodologies.
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