Staff Engineer, Software
New
A
AlphaSenseAI market intelligence
Remote - IndiaFull-TimeStaff
Salary not disclosed
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Job Details
- Required Skills
- AWSPythonGCPKubernetesAzureCI/CD
Requirements
- Be strong in Python, the primary backend language, and have shipped production code in at least two languages.
- Have designed and owned production systems serving real users at scale, including making consequential architectural decisions.
- Have led cross-team technical initiatives without formal authority, such as migrations, platform changes, or architectural shifts.
- Demonstrate strong system design instincts across failure modes, data flow, scalability, and operational cost.
- Bring deep DevOps and operational experience with Kubernetes, cloud infrastructure (AWS, Azure, or GCP), CI/CD, and observability.
- Have a track record of mentoring engineers and raising team standards through pairing, reviews, RFCs, and leading by example.
- Experience with large-scale migrations or platform rewrites is a plus.
- Hands-on production experience with AI/ML, such as LLMs, BERT, NLP pipelines, or document understanding systems, is a plus.
- Experience with content processing, enrichment, or search systems at scale is a plus.
- Familiarity with Java, GitOps, ArgoCD, or Infrastructure as Code is a plus.
Responsibilities
- Set technical direction, make build-versus-buy decisions, define architecture, and own the technical roadmap alongside product leadership.
- Turn ambiguous problems into executable plans by scoping work, identifying risks, breaking initiatives into deliverable increments, and aligning teams.
- Design and deliver scalable pipelines, robust services, and high-performance production systems.
- Use AI-assisted development tools, including Claude Code, Cursor, and Copilot, as part of the engineering workflow.
- Evaluate and integrate AI/ML capabilities such as LLMs, embeddings, and classification models into production systems when appropriate.
- Lead cross-team technical initiatives, RFCs, architectural reviews, and consensus-building on technical decisions.
- Own systems from requirements through release and production, monitor SLOs/SLIs, troubleshoot issues, and improve reliability.
- Raise engineering standards through code reviews, mentorship, and technical documentation.
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