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Est. Monthly
Estimated €5,500 - €7,000
Posted August 7, 2026 · 0 days agoLast seen August 7, 2026Est. expiry September 11, 2026

Software Engineer

Staff Software Engineer
Remote - India
Remote · Software Engineering
Full-time · Senior
English
No People Management
How this salary compares
Salary Context: Software Engineer

Hover or tap a row for full statistics (EUR / month on this chart).

Salary analysis

Compared with the selected benchmark ("Market Average: Senior Level"), this listing's salary midpoint is about 94% lower. The offer sits below the benchmark range (€5,000–€12,622). The listed pay band (€458–€583) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 53 comparable listings.

Monthly salary comparison for Software Engineer
MarketLower bound (25th percentile)MedianUpper bound (75th percentile)
Market Average: Software Engineer€3,500/per month€5,750/per month€12,307/per month
Pay in our data — not quoted in ad (Senior)€458/per month€521/per month€583/per month
About the role

About the Role We're looking for a Staff Software Engineer who owns technical direction, thrives in ambiguity, and uses AI as a natural part of how they build software. You won't just write code - you'll make decisions that shape systems for years, mentor engineers across teams, and drive the engineering bar higher across the organization. This role sits within the Unstructured Content Portfolio, Broker Research domain - the systems that acquire, process, and deliver equity research from major brokers, and the authorization layer that controls who can access what. You'll work on real-time ingestion pipelines, multi-vendor API integrations, entitlement enforcement across distributed systems, and content delivery at scale - where compliance, reliability, and low-latency processing matter deeply. As a Staff Engineer, you'll operate at the intersection of technical depth and organizational influence - turning ambiguous business problems into executable technical strategies, and shipping them end-to-end. What You'll Do - Set technical direction for your area - make build-vs-buy decisions, define architecture, and own the technical roadmap alongside product leadership. - Take ambiguous problems and make them concrete - scope work, identify risks, break down large initiatives into deliverable increments, and drive alignment across teams. - Design and deliver production-grade systems - scalable pipelines, robust services, and high-performance solutions that serve real users at scale. - Leverage AI tools as part of your workflow - you use AI-assisted development (Claude Code, Cursor, Copilot) to accelerate your work and have formed opinions on when it helps and when it gets in the way. - Evaluate and integrate AI/ML capabilities into production systems when the problem calls for it - you don't need to be an ML researcher, but you're sharp enough to pick up LLMs, embeddings, or classification models and put them to work. - Drive cross-team technical initiatives - influence engineers and teams you don't manage. Lead RFCs, drive architectural reviews, and build consensus on hard technical decisions. - Own what you build - from requirements to release to production. You build it, you run it. You monitor SLOs/SLIs, troubleshoot production issues, and continuously improve reliability. - Raise the engineering bar - through code reviews, mentorship, technical documentation, and by modeling the standards you expect from others. Must Have - Strong in Python (our primary backend language). Comfortable working across languages - you've shipped production code in at least two. - Designed and owned production systems serving real users at scale - not just contributed to them, but made consequential architectural decisions and lived with the outcomes. - Led cross-team technical initiatives without formal authority - driven migrations, platform changes, or architectural shifts that required aligning multiple teams. - Strong system design instincts - you think in terms of failure modes, data flow, scalability, and operational cost. You design for the system you'll maintain, not just the one you'll ship. - Deep DevOps and operational experience - Kubernetes, cloud infrastructure (AWS/Azure/GCP), CI/CD, observability. You don't throw code over the wall. - Track record of mentoring engineers and raising team standards - through pairing, reviews, RFCs, and leading by example. Good to Have - Experience leading large-scale migrations or platform rewrites - Hands-on experience with AI/ML in production - LLMs, BERT, NLP pipelines, or document understanding systems - Contributed to or driven engineering-wide standards, practices, or tooling - Experience with content processing, enrichment, or search systems at scale - Familiarity with Java (parts of our stack) - Experience with GitOps, ArgoCD, or Infrastructure as Code - Active practitioner of AI-assisted development (AIDLC) - uses AI tools daily in their engineering workflow

Job Details

Responsibilities

  • Set technical direction, define architecture, and own the technical roadmap
  • Translate ambiguous business problems into concrete technical strategies and deliverable increments
  • Design and deliver scalable, production-grade pipelines and high-performance services
  • Utilize AI-assisted development tools (Claude Code, Cursor, Copilot) to accelerate workflow
  • Integrate AI/ML capabilities such as LLMs, embeddings, or classification models into production systems
  • Lead cross-team technical initiatives, RFCs, and architectural reviews
  • Own the full lifecycle of built systems from requirements to production monitoring (SLOs/SLIs)
  • Raise engineering standards through code reviews, mentorship, and technical documentation

Requirements

  • Strong proficiency in Python
  • Experience shipping production code in at least two different languages
  • Proven track record of designing and owning production systems serving users at scale
  • Experience leading cross-team technical initiatives without formal authority
  • Strong system design instincts regarding failure modes, data flow, and scalability
  • Deep DevOps and operational experience with Kubernetes, cloud infrastructure (AWS/Azure/GCP), CI/CD, and observability
  • Experience mentoring engineers and raising team standards

Skills & Technologies

PythonKubernetesAWSAzureGCPCI/CDLLMsClaude CodeCursorCopilotJavaGitOpsArgoCDInfrastructure as Code
Seen 22 hours agoContent Complete
Financial overview
€28.2M
Revenue
€14.9M
Profit
0.5%
Profit margin
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AlphaSenseOy · 204 open roles
Top locations: Remote - Global · 177 · Helsinki, Finland · 17 · Singapore · 2+6 other locations
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