{"id":3712170,"url":"https://alion.io/job/selector-senior-softwaresolutions-engineer","title":"Senior Software/Solutions Engineer","company":{"id":1944457,"name":"Selector","domain":"selector.ai","url":"https://alion.io/company/selector-ai","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":{"grade":"B","score":77,"open_postings":13,"ghost_share":0.308,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":155,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":185000,"currency":"USD","period":"year","gross":null,"usd_annual":185000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Ansible","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Go","optional":false},{"name":"Python","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"DHCP","optional":true},{"name":"DNS","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-11-03T23:45:20Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T18:38:36Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":0},"description":"Senior Software Engineer\nAbout Us\nSelector is building an operational intelligence platform for digital infrastructure. Using an AI/ML-based analytics approach, the platform provides actionable, multi-dimensional insights to network, cloud, and application operators. It helps operations teams meet their KPIs through seamless collaboration, a search-driven conversational experience, and automated data engineering pipelines.\nOur solutions are used by leading Telecom, Media, Health Care, Finance, Retail, Professional Sports, and Fortune 500 enterprise organizations around the world. Our novel approach and rapidly expanding footprint position us for continued growth as a category leader.\nPerks: discretionary PTO, health insurance, 401k, bonus potential, and more.\nAbout the Role\nThis is a backend-heavy role for experienced engineers who want to solve complex data and systems problems - and see that work run in production, inside a customer's environment, not just in a sprint backlog. You'll build and maintain the ETL pipelines, data models, and integrations that power Selector's platform, applying agentic AI workflows to help infrastructure reason about itself at scale, while providing technical leadership and mentorship to engineers around you.\nYou'll also work directly with customers to understand their data and environment, translating complex technical concepts into solutions that fit their specific, high-stakes infrastructure - so your backend work isn't abstract, it's solving a real problem for a real team.\nResponsibilities\nDesign, write, and maintain production grade Python/Go code for ETL pipelines, data models, and platform integrations.\nApply agentic AI workflows to automate data engineering, correlation, and root-cause analysis across complex infrastructure data.\nProvide technical leadership on architecture and design decisions, setting the technical direction for backend systems and integrations.\nMentor and guide junior and mid-level engineers, reviewing code and helping raise the technical bar across the team.\nBuild backend logic connecting Selector's platform to customer data sources, APIs, and existing tooling.\nWork directly with customers to understand complex data structures, workflows, and analytics requirements, translating them into technical solutions.\nLead hands-on integration and deployment of Selector's platform to meet customer requirements, partnering with sales and customer teams.\nHelp ensure customers are enabled for use and basic self-serve extensions of Selector's capabilities.\nDrive pre-sales activities and Proof of Concept (POC) builds, shaping technical strategy in collaboration with the sales team.\nDocument customer feedback and translate it into concrete product and engineering improvement proposals.\nYou Will Thrive If You\nEnjoy backend engineering - especially ETL, data pipelines, and complex system design - and want to see your work run in front of real customers.\nLike applying AI/agentic workflows to solve genuinely hard, ambiguous problems, not just well-defined ones.\nNaturally lead by example and enjoy mentoring other engineers, without needing a formal management title to do it.\nRemain hands-on with testing and automation even as you take on more architectural and leadership responsibility.\nCan evaluate whether a system output is truly correct, not just whether a test passed.\nBalance quality, speed, and pragmatism when building under real customer constraints.\nBuild processes that improve quality without introducing unnecessary overhead.\nEnjoy solving complex technical problems and working closely with both engineering and customer teams.\nRequirements\nBachelor's degree or higher in Computer Science, Engineering, or a related field.\n3-7 years of professional experience in a technical or engineering role, including experience owning systems end-to-end.\nStrong coding skills in Python, with deep experience building ETL pipelines and working with complex data structures; exposure to Ansible or Go is a plus.\nDemonstrated technical leadership experience - leading projects, mentoring engineers, or setting technical direction, with or without a formal title.\nSolid working knowledge of public cloud platforms such as AWS, GCP, or Azure.\nHands-on experience with containerization technologies such as Docker and Kubernetes.\nStrong SQL skills for data extraction and analysis; familiarity with Jupyter notebooks is a plus.\nExperience with or strong interest in agentic AI workflows and applying them to real-world engineering problems.\nStrong communication skills, both verbal and written, with experience working in a customer-facing environment.\nSolid understanding of networking concepts (e.g., Data Center, WAN, DNS/DHCP).\nA self-starter attitude and the ability to thrive in a fast-paced, collaborative environment.\nCompensation\nThe salary for this role is $150,000 - $185,000. 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