Specialist Software Engineer
On-site · Hyderabad, Telangana, India
Job Summary
Specialist Software Engineer will design, develop, and evolve AI-powered scientific authoring platforms for Research and Preclinical organizations; lead architecture decisions for scalable, secure, and compliant AI solutions; build Retrieve-Augmented Generation pipelines, vector search, semantic retrieval, multi-agent workflows, and grounding mechanisms; implement document ingestion, embedding, and indexing; develop prompt orchestration and agent execution frameworks; leverage AWS and cloud-native practices; collaborate with scientists, informaticians, product managers, and engineers to accelerate research and knowledge management.
Required Qualifications
- Master's or Bachelor's degree and 8-12 years of Information Systems experience
- 8+ years of software engineering experience
- 2+ years of hands-on experience developing Generative AI or LLM-powered applications implementing RAG concept
- Strong proficiency in Python
- Experience developing scalable backend applications using Python, Java, or related technologies
- Strong API design and microservices development experience
- Strong SQL skills and database design experience
- Hands-on experience with Large Language Models (LLMs) and Generative AI platforms
- Experience implementing RAG architectures and semantic retrieval systems
- Experience with vector databases such as PGVector, Pinecone, Weaviate, or OpenSearch Vector
- Experience with LangGraph, Semantic Kernel, CrewAI, or equivalent
- Strong understanding of prompt engineering, grounding, and AI evaluation methodologies
- Hands-on experience with AWS services such as S3, RDS, ECS/EKS, Lambda, IAM, CloudWatch, and EventBridge
- Experience building cloud-native and distributed systems
- Experience with containerization technologies including Docker and Kubernetes
- Experience with scientific document processing and OCR technologies
- Experience with Amazon Bedrock, OpenAI, Anthropic Claude, or equivalent AI platforms
- Experience with Terraform, CloudFormation, or Infrastructure as Code (IaC) practices
- Experience with CI/CD pipelines and DevOps methodologies
- Experience with monitoring and observability tools such as Splunk, Grafana, Prometheus, Datadog, or CloudWatch
- Experience with scientific authoring, regulatory content management, PKDM, Toxicology, or Research Informatics platforms
- AWS Certified Solutions Architect – Associate or Professional AWS Machine Learning Specialty
- Kubernetes certifications (CKA/CKAD)
- Strong problem-solving and analytical skills
- Ability to translate complex scientific and business requirements into technical solutions
- Excellent communication and stakeholder management skills
- Ability to work effectively with global cross-functional teams
- High degree of ownership and technical leadership
- Ability to influence architecture and engineering decisions
- Strong mentoring and collaboration skills
- Ability to manage multiple priorities in a fast-paced environment
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