Software Engineering Advisor

1 week ago

Hyderabad, Telangana, India Evernorth Full time

ABOUT EVERNORTH:

Evernorth exists to elevate health for all, because we believe health is the starting point for human potential and progress. As champions for affordable, predictable and simple health care,
we solve the problems others dont, wont or cant.

Our innovation hub in India will allow us to work with the right talent, expand our global footprint, improve our competitive stance, and better deliver on our promises to stakeholders. We are passionate about making healthcare better by delivering world-class solutions that make a real difference.

We are always looking upward. And that starts with finding the right talent to help us get there.

Role Title: Software Engineering Advisor

Position Summary:

The GenAI Data Engineer will be responsible for designing, developing, testing, and deploying data pipelines and ETL processes to collect, clean, and integrate GenAI-related data from various sources into the data storage system. They will also be responsible for implementing data quality control and data management procedures, monitoring, and optimizing the performance of data pipelines and ETL processes and collaborating with cross-functional teams to provide data engineering support for ad-hoc data analysis requests and analytics projects. The ideal candidate should have 1-3 years of experience in data engineering with a focus on GenAI and deep learning technologies, proficiency in ETL tools and frameworks, and strong programming skills in languages such as Python, Java, or Scala.

Job Description & Responsibilities:

  • Build scalable software solutions using LLMs and other ML models to solve challenges in healthcare.
  • Build enterprise grade AI solutions with focus on privacy, security, fairness.
  • Work with Product Development as a Generative Artificial Intelligence (AI) subject matter expert and architect and develop scalable, resilient, ethical AI solutions.
  • Strong engineering skills to design the output from the AI with nodes and nested nodes in JSON or array, HTML formats as required This is critical so that the AI output can be consumed as is and displayed on the dashboard for accelerated development cycles.
  • Build extensible API Integrations, low code UI/UX solutions, with extremely short cycle times, to extract information from sources, integrate with GPT4, receive insights and make them available in intuitive, high performing dashboards.
  • Build solutions that align with responsible AI practices.
  • Envision the solution outcomes to solve for the business problem with actionable insights and design viable solutions to meet the outcomes.
  • Understand how AI is interpreting the data set and use that understanding to build prompts that lead to expected outcomes.
  • Architect and develop software or infrastructure for scalable, distributed systems and with machine learning technologies.
  • Work with frameworks (Tensorflow, PyTorch) and open-source platforms like Hugging Face to deliver the best solutions.
  • Optimize existing generative AI models for improved performance, scalability, and efficiency.
  • Develop and maintain AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.
  • Develop clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.
  • Contribute to the establishment of best practices and standards for generative AI development within the organization.

Experience Required:

  • 1 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
  • 1-2 years of experience in data engineering, focusing on GenAI and deep learning technologies, preferably within the healthcare industry or a related domain.

Experience Desired:

  • Experience in implementing enterprise systems in production setting for AI, computer vision, natural language processing. Exposure to self-supervised learning, transfer learning, and reinforcement learning is a plus.
  • Experience with information storage/retrieval using vector databases like pinecone.
  • Experience with designing scalable software systems for classification, text extraction/summary, data connectors for different formats (pdf, csv, doc, etc)
  • Experience with machine learning libraries and frameworks such as PyTorch or TensorFlow, Hugging Face, Lang chain, Llama Index.
  • Experience working with cross-functional global teams, including collaboration with IT, analytics, and business stakeholders, developing strong working relationships and deep partnerships with the business.

Education and Training Required:

  • University degree in a quantitative field, such as Statistics, Math, Economics, Engineering, Computer Science, Business Analytics, Data Science, or a relevant field.

Primary Skills:

  • Strong understanding and exposure in natural language generation or Gen AI like transformers, LLMs, text embeddings.
  • Programming experience in C/C++, Java, Python.
  • Strong knowledge of data structures, algorithms, and software engineering principles.
  • Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.
  • Experience in Jira and Confluence is a must.
  • Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
  • Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
  • Possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment.

Additional Skills:

  • Knowledge of healthcare industry standards, regulations, and data privacy practices, such as HIPAA, GDPR, and others.
  • Understanding of the healthcare domain, including medical terminology, clinical data, patient records, and industry trends related to GenAI.
  • 2 years of Full stack engineering expertise with languages like C#, Python and Proficiency in designing architecture, building API Integrations, configuring and deploying cloud services, setting up authentication, monitoring and logging.

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