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Strong Tier-1 brand, common Software Engineer title, mid-level range, metro locations, and broad skillset requirements drive high competition.
Core backend skills transfer across industries, though life-sciences/regulatory knowledge increases role-specific fit moderately.
Explicit years (3+), core backend skills and AI-fluency expectations create moderate gating without extreme specialization.
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Build and deploy high-quality software integrating AI agents into life sciences workflows, focusing on clinical data, patient services, and regulatory operations.
Lead technical architecture and design decisions; mentor engineers; own production system reliability and incident resolution (SMTS and above).
Define multi-quarter architecture roadmaps and AI tool integration strategies; ensure security and code quality in AI-augmented development (LMTS level).
3+ years of software engineering experience (MTS: 3–5 yrs; SMTS: 5–8 yrs; LMTS: 8+ yrs) with production software delivery.
Proficiency in Java, Python, Go, or JavaScript/TypeScript with experience in RESTful APIs, microservices, distributed systems, databases, and cloud platforms (AWS/GCP/Azure).
Experience with CI/CD pipelines, version control (Git), DevOps practices, and AI-assisted development tools with advanced prompt engineering skills.
Work Experience Required: 3+ years, Notice Period: Not explicitly mentioned in the JD.
Experienced software engineer comfortable driving architectural and technical decisions in AI-augmented, regulated life sciences environments.
Skilled in integrating complex AI workflows and ensuring secure, compliant software delivery in healthcare/pharma domains.
Capable of mentoring engineers in AI-tool utilization and collaborating cross-functionally to translate regulatory requirements into scalable systems.